System for configuring remittances for user-sourced crime information

ABSTRACT

A server computing device configured to receive, via an anonymization network and from a first mobile computing device that determines a location from a set of locations of the first mobile computing device is within a threshold distance of an event, a proximity indication that a first user associated with the first mobile computing device is proximate to the event; in response to receiving an indication of a remittance for the event from a second user, generate an association between the remittance and the event; in response to receiving descriptive data that is descriptive of the event, send the descriptive data to a second mobile computing device of the second user; and in response to receiving an indication to release the remittance, send a message that executes a transaction that transfers at least a portion of the amount of the remittance to an account associated with the first user.

TECHNICAL FIELD

This disclosure relates to computer networks and, more specifically, toanonymizing data traffic traversing computing networks.

BACKGROUND

Some computing devices provide a graphical user interface to outputcontent for display and receive input from a user to interact with thecomputing device. In some instances, these computing devices may alsocommunicate with one another using one or more networks. Communicationsbetween computing devices using such networks may rely on one or morenetwork protocols, such Transmission Control Protocol (TCP) and InternetProtocol (IP), to transmit data. In some instances, users may share datawith one another using one or more content sharing platforms. Contentsharing platforms may include instant messaging networks, socialnetworks, and electronic mail. Service operators of content sharingplatforms may store data that personally identifies each user'scomputing device (or user itself) and may log or otherwise track deviceinformation about each user computing device that accesses the contentsharing platforms. As such, content provided to these content sharingplatforms are traceable to the submitting user computing devices, suchthat the identities of the owners or users of these user computingdevices may be discovered.

SUMMARY

Techniques of this disclosure are directed to an anonymization overlaynetwork (or “anonymization network”) for de-identification ofevent-proximity data. In some examples, multiple different mobilecomputing devices (e.g., smartphones) assigned to different users mayinclude respective user applications that communicate over ananonymization network to a server computing device. The server computingdevice may operate a service in which each respective user applicationis assigned a user identifier that does not or cannot personallyidentify a user of the mobile computing device that includes the userapplication. Using the user identifier, the user application mayanonymously send the locations of the mobile computing device over theanonymization network to the server computing device.

The server computing device, which cannot personally identify a mobilecomputing device or the user, but can distinguish between differentusers that use the service, may determine whether a location of themobile computing device is within a threshold time and thresholddistance of an event that has occurred and generate a proximityindication that the mobile computing device was proximate to the event.In response to the user submitting descriptive data that is descriptiveof the event, the server computing device may broadcast or otherwisedistribute the descriptive data to other user applications that accessthe same service of the server computing device. These other userapplications may output for display the descriptive data in associationwith the proximity indication and the user identifier of the user thatsubmitted the descriptive data. In some examples, the system mayassociate incognito or anonymous remittances with an event that arereleased to submitters of descriptive data (e.g., users in closeproximity to a crime).

Rather than operating in a way that could personally identify or permitdiscovery of the personal identity of a user who provides descriptivedata of an event, the system described in this disclosure operatesfundamentally differently than conventional content sharing platforms byintegrating anonymous user identifiers with an anonymization network topermit the exchange of data that are descriptive of events. By providingan end-to-end, anonymous communication channel in which incognitoremittances can be released to users who exchange data that aredescriptive of events, the techniques of this disclosure may improve thesecurity of data exchanged between mobile computing devices and canincrease the privacy of users on the system. Furthermore, by providingincreased data security and privacy using an anonymization network andanonymous user identifier with incognito remittances to create anend-to-end, anonymous communication channel, techniques of thisdisclosure may enable and/or incentivize users to exchange data that aredescriptive of events, which would not otherwise be exchanged if suchsecurity, privacy, and integrated remittance distribution were notintegrated a system that provides an intuitive, efficient, and secureuser experience.

In some examples, a system includes a plurality of mobile computingdevices associated with a plurality of respective users; ananonymization network; at least one server computing devicecommunicatively coupled to each mobile computing device of the pluralityof mobile computing devices, and wherein each respective mobilecomputing device of the plurality of mobile computing devices sends,using the anonymization network, a respective set of locations of therespective mobile computing to the at least one server computing device,such that the plurality of mobile computing devices are anonymous to theat least one server computing device; wherein the at least one servercomputing device, based at least in part on a determination that alocation from a set of locations of one of the mobile computing devicesis within a threshold distance of a location of an event, generates aproximity indication that a user associated with the one of the mobilecomputing devices is proximate to the event; wherein the at least oneserver computing device, in response to receiving an indication of aremittance for the event from at least one other user, stores anassociation between the remittance and the event; wherein the at leastone server computing device, in response to receiving, using theanonymization network, descriptive data generated by the user that isdescriptive of the event, sends the descriptive data to at least oneother mobile computing device of the plurality of computing devices thatis associated with the at least one other user; and wherein the servercomputing device performs at least one operation that provides theremittance to the user in response to receiving, from the at least oneother mobile computing device that outputs a user interface in which thedescriptive data is associated with the proximity indication, anindication to release the remittance provided by the at least one otheruser.

In some examples, a server computing device includes one or morecomputer processors; and a memory comprising instructions that whenexecuted by the one or more computer processors cause the one or morecomputer processors to: receive, using an anonymization network and froma respective mobile computing device of a plurality of mobile computingdevices, a respective set of locations of the respective mobilecomputing device, such that the respective mobile computing device isanonymous to the at least one server computing device; generate, basedat least in part on a determination that a location from the respectiveset of locations of the respective mobile computing device is within athreshold distance of a location of an event, a proximity indicationthat a user associated with the respective mobile computing device isproximate to the event; in response to receiving an indication of aremittance for the event from at least one other user, generate anassociation between the remittance and the event; in response toreceiving, using the anonymization network, descriptive data generatedby the user that is descriptive of the event, send the descriptive datato at least one other mobile computing device of the plurality of mobilecomputing devices that is associated with the at least one other user;and perform at least one operation that provides the remittance to theuser in response to receiving, from the at least one other mobilecomputing device that outputs a user interface in which the descriptivedata is associated with the proximity indication, an indication torelease the remittance provided by the at least one other user.

In some examples, a mobile computing device includes one or morecomputer processors; and a memory comprising instructions that whenexecuted by the one or more computer processors cause the one or morecomputer processors to: send, using an anonymization network and to aserver computing device, a respective set of locations of the mobilecomputing device, such that the mobile computing device is anonymous tothe server computing device, and wherein the respective set of locationsare usable by the server computing device to generate, based at least inpart on a location from a set of locations being within a thresholddistance of a location of an event, a proximity indication that a userassociated with the mobile computing devices is proximate to the event;in response to receiving an indication of a remittance for the eventfrom the server computing device, contemporaneously output for displayan indication of the remittance in association with an indication of theevent; in response to receiving descriptive data generated by the userthat is descriptive of the event, send, using the anonymization network,the descriptive data to the server computing device, and output a userinterface in which the descriptive data is associated with the proximityindication; and in response to receiving, from the server computingdevice, a message that the remittance is provided to the user, outputfor display an indication that the remittance is provided to the user.

The details of one or more examples are set forth in the accompanyingdrawings and the description below. Other features, objects, andadvantages of the disclosure will be apparent from the description anddrawings, and from the claims.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a conceptual diagram illustrating an example system with andanonymization overlay network for de-identification of crime-proximitydata, in accordance with one or more aspects of the present disclosure.

FIG. 2 is a block diagram illustrating further details of a servercomputing device shown in FIG. 1 , in accordance with one or moreaspects of the present disclosure.

FIG. 3 is a block diagram illustrating further details of a mobilecomputing device shown in FIG. 1 , in accordance with one or moreaspects of the present disclosure.

FIG. 4 is a conceptual diagram of a prediction component, in accordancewith techniques of this disclosure.

FIG. 5 is a flow diagram illustrating example operations of a servercomputing device, in accordance with techniques of this disclosure.

FIG. 6 is a flow diagram illustrating example operations of a mobilecomputing device, in accordance with techniques of this disclosure.

FIG. 7 illustrates a crime map graphical user interface that may beoutput by a mobile computing device in accordance with techniques ofthis disclosure.

FIG. 8 illustrates a crime list summary graphical user interface thatmay be output by a mobile computing device in accordance with techniquesof this disclosure.

FIG. 9 illustrates a crime discussion graphical user interface that maybe output by a mobile computing device in accordance with techniques ofthis disclosure.

FIG. 10 illustrates a submit bounty graphical user interface that may beoutput by a mobile computing device in accordance with techniques ofthis disclosure.

FIG. 11 illustrates a private message summary graphical user interfacethat may be output by a mobile computing device in accordance withtechniques of this disclosure.

FIG. 12 illustrates a private message graphical user interface that maybe output by a mobile computing device in accordance with techniques ofthis disclosure.

FIG. 13 illustrates a release payment graphical user interface that maybe output by a mobile computing device in accordance with techniques ofthis disclosure.

FIG. 14 illustrates a user graphical user interface that may be outputby a mobile computing device in accordance with techniques of thisdisclosure.

The details of one or more examples of the disclosure are set forth inthe accompanying drawings and the description below. Other features,objects, and advantages of the disclosure will be apparent from thedescription and drawings, and from the claims.

DETAILED DESCRIPTION

FIG. 1 is a conceptual diagram illustrating an example system 100 withan anonymization overlay network for de-identification ofcrime-proximity data, in accordance with one or more aspects of thepresent disclosure. FIG. 1 includes a conceptual diagram of a map 102 ofa city that includes roads (e.g., road 104) and city blocks (e.g., cityblock 106). In some examples, roads may be sidewalks, pathways,railways, or any other area designated for traveling from one locationto another. City blocks may include buildings, parks, or any otherregions that are not roads. Although described with respect to roads andcity blocks in FIG. 1 , techniques of this disclosure may be used in anygeographic setting, which may or may not include roads and city blocks.

Map 102 further illustrates users 108A and 108B (“users 108”). Users 108may work, travel, and otherwise live at various different locationsrepresented by map 102. Users 108 may each own, carry, and/or use one ormore mobile computing devices. For instance user 108A may own, carry,and use mobile computing device 110A and user 108B may own, carry, anduse mobile computing device 110B. Mobile computing devices 110A and 110Bmay be referred to as mobile computing devices 110. Map 102 furtherillustrates crime location 112 which may be a location of a crime. Map102 may include any number of crime locations. In some examples, crimelocation may be a location where a crime has occurred or where a crimeis suspected to occur. In some examples, an event location (not shown)may be included in map 102. An event location may be a crime location ormay be any location of interest where an event occurred. For instance,an event may not be a crime. An event may be a mass gathering, assembly,congregation of people of a threshold size in a region or location, anoccurrence at a region or location, and/or any other happening at a timeor during a time range and/or at location or region. Although describedwith respect to a crime location in FIG. 1 , techniques of thisdisclosure may be applied to any event location.

In the example of FIG. 1 , mobile computing devices 110 may besmartphones. In some examples, a smartphone may be a mobile personalcomputer with an operating system and one or more applications. Furtherdetails of mobile computing devices 110 are described in FIG. 3 . Inother examples, mobile computing devices 110 may be wearable computingdevices such as smartwatches, computerized fitness band/trackers,computerized eyewear, computerized headwear, computerized gloves, andthe list. In other examples, mobile computing devices 110 may be anytype of mobile computing device that can attach to and be worn on aperson's body or clothing. In still other examples mobile computingdevices 110 may be tablet computers, personal digital assistants (PDA),game systems or controllers, media players, e-book readers, televisionplatforms, navigation systems, remote controls, or other mobile computerthat can easily be moved by a user.

Mobile computing devices 110 may include one or more components. Somecomponents described herein use software, hardware, firmware, or amixture of both hardware, software, and firmware residing in andexecuting on mobile computing devices 110 or at one or more other remotecomputing devices (e.g., server computing devices 116) to perform theoperations and provide the functionality described in this disclosure.Mobile computing devices 110 may execute instructions of some components(e.g., implemented with a mixture of hardware, software, and/orfirmware) with one or more processors. Mobile computing devices 110 mayexecute instructions of some components as or within a virtual machineexecuting on underlying hardware. As described herein, components may beimplemented in various ways. For example, some components may beimplemented as a downloadable or pre-installed application or “app.” Inother examples, some components may be implemented as part of anoperating system of a mobile computing device.

FIG. 1 further illustrates data center 114. Data center 114 includesmultiple server computing devices 116A, 116B, 116C (“server computingdevices 116”), which collectively may provide one or more services ofserver application 130. In some examples, a service provider may operateand administrate the one or more services. Although three servercomputing devices are shown for example purposes in FIG. 1 , any numberof server computing devices may be included in data center 114. In someexamples, each of server computing devices 116 may be communicativelycoupled to one another and/or to network 118. In some examples, servercomputing devices 116 may be communicatively coupled to one anotherwithin data center 114 and/or to network 118 using one or more networkdevices, such as switches, routers, and hubs (not shown) that areinterconnected using one or more communication link, which may be wiredand/or wireless. Examples of communication links may be CAT-5, CAT-6,CAT7 or any other physical links. Examples of communication links maywireless connections such as WiFi, 4G LTE, and/or any other wirelesslinks.

As further described in this disclosure, server computing devices 116may include one or more components. Some components described herein usesoftware, hardware, firmware, or a mixture of both hardware, software,and firmware residing in and executing on server computing devices 116or at one or more other remote computing devices (e.g., mobile computingdevices 110) to perform the operations and provide the functionalitydescribed in this disclosure. Server computing devices 116 may executeinstructions of some components (e.g., implemented with a mixture ofhardware, software, and/or firmware) with one or more processors. Servercomputing devices 116 may execute instructions of some components as orwithin a virtual machine executing on underlying hardware.

FIG. 1 illustrates network 118. Network 118 represents a publiclyaccessible computer network that is owned and operated by a serviceprovider, which is usually large telecommunications entity orcorporation. Network 118 is usually a large layer three (L3) computernetwork, where reference to a layer followed by a number refers to acorresponding layer in the Open Systems Interconnection (OSI) model.Network 118 is a L3 network in the sense that it natively supports L3operations as described in the OSI model. Common L3 operations includethose performed in accordance with L3 protocols, such as the Internetprotocol (IP).

Network 118 may provide access to the Internet, and may allow thecomputing devices within different customer networks to communicate witheach other. Network 118 may include a variety of network devices otherthan PEs 10. Although additional network devices are not shown for easeof explanation, it should be understood that network 118 may compriseadditional network and/or computing devices such as, for example, one ormore additional switches, routers, hubs, gateways, security devices suchas firewalls, intrusion detection, and/or intrusion prevention devices,servers, computer terminals, laptops, printers, databases, wirelessmobile devices such as cellular phones or personal digital assistants,wireless access points, bridges, cable modems, application accelerators,or other network devices. Moreover, although the some elements of system100 are illustrated as being directly coupled, it should be understoodthat one or more additional network elements may be included along anycommunication links or channels such that the network elements of system100 are not directly coupled.

FIG. 1 further illustrates anonymization network 120. Anonymizationnetwork 120 may include one or more relays (e.g., relays 122A, 122B andother relays delineated within anonymization network 120, collectively“relays 122” or “relay network devices”), where each relay is acomputing device, such as a desktop computing device, laptop, mobilecomputing device, server, or any other computing device. Each of relays122 may include a component or application that communicates with one ormore other relays to establish a route from a source device (e.g., 110B)that sends data to a destination device (e.g., data center 114 or servercomputing device 116C within data center 114) and anonymize the sourcedevice from the destination device.

In some examples, onion routing is implemented within anonymizationnetwork 120 such that encryption in the application layer of acommunication protocol stack encrypts data, including the next node(e.g., relay) destination IP address, one or more times and sends itthrough a virtual circuit comprising successive, randomly selectedrelays. In some examples, each relay decrypts a layer of encryption toreveal only the next relay in the circuit in order to pass the remainingencrypted data on to it. The final relay decrypts the innermost layer ofencryption and sends the original data to its destination withoutrevealing, or even knowing, the source IP address. Because the routingof the communication is partly concealed at one or more hops in thecircuit, onion routing may eliminate any single point at which thecommunicating peers can be determined through network surveillance thatrelies upon knowing its source and destination. In some examples,anonymization network 120 may be implemented with software executing onone or more relays that conforms to the Tor Protocol Specification,https://gitweb.torproject.org/torspec.git/tree/tor-spec.txt, Aug. 2,2017, which is hereby incorporated by reference in its entirety.

For illustration purposes, anonymization network 120 may include acomponent or application that implements the Tor Protocol Specificationat each of relays 122, although anonymization network 120 may beimplemented with any other component, application, and/or specificationthat anonymizes the source device from the destination device. Forinstance, in another example, anonymization network may be implementedwith software executing on one or more relays that conform to I2PProject Specifications, https://geti2p.net/spec, Aug. 2, 2017, which ishereby incorporated by reference in its entirety. Although anonymizationnetworks are illustrated for example purposes in FIG. 1 , any technique,component, and/or implementation that anonymizes the source device fromthe destination device may be used, whether implemented as anonymizationnetwork or otherwise. In some examples, a Virtual Private Network,FreeNet, Whonix, or any other suitable component and/or network thatanonymizes the source device from the destination device may be used.The operation of anonymization network 120 in accordance with techniquesof this disclosure is further described herein.

In the example of FIG. 1 , anonymization network 120 includes an ingressrelay network device 122B communicatively coupled to mobile computingdevice 110B. An ingress relay network device may the entry point of datasent by mobile computing device 110B into anonymization network 120.Anonymization network 120 may include an egress relay network device122C communicatively coupled to at least one server computing device indata center 114. An egress relay network device may be an exit pointfrom anonymization network 120 for data sent by mobile computing device110B. Anonymization network 120 may include one or more intermediaterelay network devices, such as intermediate relay network device 122D.Ingress relay network device 122B, intermediate relay network devices(e.g., device 122D), and egress relay network device 122C maycollectively provide a communication route between the mobile computingdevice 110B and the at least one server computing device in data center114. In some examples, descriptive data is received by ingress relaynetwork device 122B from the mobile computing device 110B, and eachrelay network device in the set of relay network devices encrypts thedescriptive data before the descriptive data is forwarded to anotherrelay network device in the communicate route. In some examples, egressrelay network device 122C decrypts the descriptive data and forwards thedescriptive data to the at least one server computing device in datacenter 114, such that the plurality of mobile computing devices areanonymous to the at least one server computing device. In some examples,a mobile computing device is anonymous to a server computing device ifit is unknown to the server computing device the identity of the mobilecomputing device on a network using an addressing system or protocol ofthe network that is used to identify computing devices. In someexamples, a user is anonymous to a server computing device if it isunknown to the server computing device, the personal identity of theuser, and/or the identity of the mobile computing device on the networkusing an addressing system or protocol of the network that is used toidentify computing devices.

FIG. 1 further illustrates crime data server 124. Crime data server 124may include one or more components and/or applications that generate,receive, store, process, and/or transmit data descriptive of crimes. Forinstance, crime data server 124 may include a datastore with one or morerecords or entities, wherein each record or entity includes datadescribing a particular crime. For instance, data describing aparticular crime may include but is not limited to: crime type, crimelocation (e.g., latitude/longitude, street address, city state, zip),crime date, crime time, or any other data that describes a crime. Insome examples, crime data server 124 may, more generally, be an eventdata server that stores event data descriptive of events. Crime dataserver 124 may provide crime data to data center 114 as described inthis disclosure. In some examples, crime data server 124 may providecrime data to data center 114 via network 118 using or not usinganonymization network 120. In some examples, crime data server 124 maybe included within data center 114 and/or functionality provided bycrime data server 124 may be included in server computing devices 116.

FIG. 1 , illustrates payment server 126. Payment server 126 mayrepresent one or more computing devices that provide payment processingservices. For instance, payment server 126 may support money transfers,which may be online or otherwise network based. As an example, servicesprovided by payment server 126 allow users to execute financialtransactions online by granting the ability to transfer fundselectronically between different users. Examples of such serviceproviders may include PayPal, Stripe, Square, Western Union, or anyother service that supports online money transfers.

In some examples, payment server 126 may facilitate cryptocurrencytransfers. A cryptocurrency may be a digital asset that operates as amedium of exchange using cryptography to secure the transactions and tocontrol the creation of additional units of the currency. Somecryptocurrencies, which may be used in accordance with techniques ofthis disclosure, such as BitCoin and Ethereum, may be blockchain-basedwhile others may not. A blockchain may be a distributed database that isused to maintain a continuously growing list of records, called blocks.Each block contains a timestamp and a link to a previous block. Ablockchain is typically managed by a peer-to-peer network collectivelyadhering to a protocol for validating new blocks. In some examples,cryptocurrencies or other forms of money transfer may anonymize therecipient of funds from the provider of such funds. In this way, theidentity of the recipient of the funds may not be known to the providerof such funds.

In accordance with techniques of this disclosure, each of mobilecomputing devices 110A, 110B may include a user application 128A, 128B(“user applications 128”), respectively, that implement techniques ofthis disclosure. Each of user applications 128 may be downloaded from anapplication store, such as the Google Play Store or the Apple App Store.User 108A, for example, may provide one or more user inputs at mobilecomputing device 110A that cause mobile computing device 110A todownload user application 128A. Upon initially executing userapplication 128A for the first time at mobile computing device 110A,user application 128A may establish a connection with server application130 executing at data center 114 via anonymization network 120. Serverapplication 130 may perform one or more techniques of this disclosure,and may execute independently or collectively one or more of servercomputing devices 116.

At first-time execution, user application 128A may send one or moretypes of information via anonymization network 120 to server application130, which application 130 may use to generate a unique user identifierfor user 108A, which is stored and used by each of application 130 anduser application 128A. In some examples, the one or more types ofinformation sent by user application 128A do not personally identify andcannot personally identify mobile computing device 110A or user 108A.For instance, the one or more types of information may be a randomnumber, a timestamp, a hash value, or any other type of information.Server application 130 may apply one or more functions or otheroperations to the one or more types of information received from mobilecomputing device 128A to generate a user identifier for user 108A. Forinstance, server application may apply a hash function, random numbergeneration function, or any other function to the one or more types ofinformation to generate the user identifier for user 108A. Accordingly,server application 130 may generate, store, and use the unique useridentifier that is associated with user 108A and/or mobile computingdevice 110A for purposes of distinguishing between different uniqueusers and/or devices in system 100, but cannot be used to personallyidentify or physically locate user 108A and/or mobile computing device110A. In this way, server application 130 may maintain identifiers fordifferent unique users and/or mobile computing device withoutmaintaining information that can be used to personally identify and/orphysically locate users or mobile computing devices that use servicesprovided by server application 130. User 108B may cause user application128B to be installed and configured in a similar matter at mobilecomputing device 110B.

In the example of FIG. 1 , each respective mobile computing device ofmobile computing devices 110 sends, using anonymization network 120, arespective set of locations of the respective mobile computing to atleast one server computing device of data center 114, such thatrespective source addresses of mobile computing devices 110 are unknownto data center 114. For example, user application 128A may determinelocation data for mobile computing device 110A. In some examples, eachinstance of location data may be associated with a metadata, such as butnot limited to: a timestamp when mobile computing device 110A wasdetected at the particular location represented by the location data, auser identifier, an elevation, an environmental condition, or any otherdata associated with or descriptive of the location. Location data ofmobile computing device 100A may be GPS coordinates (e.g., latitude andlongitude pairs), generic-named locations (e.g., “home”, “work”,“school”), literal-named locations (e.g., “1508 Westview Drive”, “TargetField”, etc.), or any other suitable encoding or representation oflocation information.

In some examples, user application 128A may detect and store locationdata periodically or according to a defined interval. For instance, userapplication 128A may detect and store location data according to ahard-coded, user-defined, and/or machine-generated interval. In exampleexamples the defined interval may be enumerated in millisecond, seconds,minutes, hours, or days, to name only a few examples. In some examples,the interval may be within a range of 1-120 minutes. In some examples,the interval may be within a range of 1 and 24 hours. In some examples,the define interval may be 5 minutes, 15 minutes, 30 minutes, 60minutes, 2 hours, 6 hours, or 12 hours. In some examples, userapplication 128A may detect and store location data according to aschedule which may be hard-coded, user-defined, and/or machinegenerated.

In some examples, user application 128A may detect and store locationdata according to one or more asynchronous events. For instance, userapplication 128A may detect and store location data for a particularlocation in response to mobile computing device 110A moving from oneunique location to a different unique location. In some examples, userapplication 128A may receive location data from a provider serviceimplemented by a runtime environment, operation system or othercomponent that provides an updated location to any listener orsubscriber component, such as user application 128A. In this way, asmobile computing device moves from one location to another, userapplication 128A may receive location data that represents the newlocation from the provider service. In some examples, mobile computingdevice 110A and/or, more particularly the provider service, may provideupdated location data for changes in location that satisfy a thresholddistance change between a prior location and a subsequent, new location.

In some examples, user application 128A sends one or more sets of one ormore instances of location data (and, in some examples, correspondingmetadata) to server application 130. User application 128A may send aset of location data as the location data is received or generated byuser application 128A, such as in real-time or near-real-time. In someexamples, user application 128A may send a set of location data inresponse in response to one or more asynchronous events. An asynchronousevent may not occur on a periodic basis or according to a defined timeinterval. Examples of asynchronous events may be but are not limited to:a storage size threshold is exceeded, a particular network type (e.g.,wifi, Ethernet, LTE, etc.) is detected, a user input is received, or anyother event that may not occur on a periodic basis or according to adefined time interval.

In other examples, user application 128A may send one or more sets oflocation data to server application 130 periodically or according to adefined interval. For instance, user application 128A may send one ormore sets of location data to server application 130 according to ahard-coded, user-defined, and/or machine-generated interval. In exampleexamples the defined interval may be enumerated in millisecond, seconds,minutes, hours, or days, to name only a few examples. In some examples,the interval may be within a range of 1-120 minutes. In some examples,the interval may be within a range of 1 and 24 hours. In some examples,the defined interval may be 5 minutes, 15 minutes, 30 minutes, 60minutes, 2 hours, 6 hours, or 12 hours. In some examples, userapplication 128A may send one or more sets of location data to serverapplication 130 according to a schedule which may be hard-coded,user-defined, and/or machine generated.

As described above, a source address of mobile computing device 110A maybe unknown to server application 130 when server application 130receives the one or more sets of location data from mobile computingdevice 110A because the one or more sets of location data aretransmitted to server application 130 using anonymization network 120.In some examples, a source address may be the source IP address formobile computing device 110A. In some examples, respective identifiersof mobile computing devices are respective source network addresses ofthe respective mobile computing devices, and the respective identifiersof the mobile computing devices are unknown to server computing devicesin data center 114.

In other examples, a non-IP based network or network that uses otheraddressing techniques in addition to or in lieu of IP, the sourceaddress may any identifier that identifies the mobile computing deviceon the network. More generally, in non-address based networks,communication channels, or any communication medium, server application130 may receive the one or more sets of location data from mobilecomputing device 110A without one or more identifiers that would enableidentification of mobile computing device 110A, except that in suchcases, the user identifier generated by server application 130 for user108A may be included with or otherwise accompany the one or more sets oflocation data. In any case, server application 130 may store the one ormore sets of location data from mobile computing device 110A inassociation with the user identifier for user 108A. Similarly, serverapplication 130 may store the one or more sets of location data frommobile computing device 110B in association with the user identifier foruser 108B.

Server application 130 may receive crime data from crime data server 124and/or generate crime data. Server application 130 may, based at leastin part on determining that a location from a set of locations of one ofthe mobile computing devices, is within a threshold distance of alocation of a crime, generate a proximity indication that a userassociated with the one of the mobile computing devices is proximate tothe crime. For instance, server application 130 may determine a distancebetween crime 112 and an instance of location data from user application128A that indicates a respective location of mobile computing device110A as shown in map 102. Server application 130 may generate thedistance as a Euclidean distance, although any suitable distancecalculation may be used. In some examples, server application 130 maydetermine a distance between crime 112 and an instance of location datafrom user application 128A that indicates a respective location ofmobile computing device 110A if server application 130 determines thatan amount of time between a timestamp of the crime and a timestamp ofthe instance of location data satisfies a time threshold (e.g., is lessthan or equal to the time threshold). Although described usingtimestamps for example purposes, any representation of time and/or datesmay be used. The time threshold may be hard-coded, user-defined, ormachine generated. In some examples, the time threshold may beenumerated in millisecond, seconds, minutes, hours, or days, to nameonly a few examples. In some examples, the interval may be within arange of 1-180 minutes. In some examples, the interval may be within arange of 1 and 24 hours. In some examples, the defined interval may be 1minute, 5 minutes, 15 minutes, 30 minutes, 60 minutes, 2 hours, 6 hours,or 12 hours.

In accordance with techniques of this disclosure, server application 130may determine a set of respective distances between each crime of a setof crimes and each instance of location data from a set of locationdata. For example, server application 130 may determine a set ofrespective distances between each crime of a set of crimes that includescrime 112 and each instance of location data from a set of location datathat was sent by user application 128A to server application 130.Further, in FIG. 1 , server application 130 determines the respectivedistances for those instances of location data having timestamps which,when compared to the timestamps of respective crimes in the set ofcrimes, have a time duration that is less than or equal to a timethreshold. In the example of FIG. 1 , the time threshold is 30 minutes,and as such, server 130 determines respective distances for thoseinstances of location data having timestamps which, when compared to thetimestamps of respective crimes in the set of crimes, are 30 minutes orless between the timestamp of respective crime and the respectiveinstance of location data. In this way, server application 130 maydetermine the respective distances between user mobile computing device110A and crime 112 when mobile computing device 110A was temporallyproximate (e.g., within the time threshold) to crime 112.

Server application 130 generate, store, provide, send, or otherwiseindicate that a user is in proximity to a particular crime. A user maybe in proximity to a crime if a location of the mobile computing deviceof the user is within a threshold distance of the particular crime. Asdescribed in this disclosure, a mobile computing device may receive datafrom server application 130 that enables the mobile computing device toindicate that at least one other user was in proximity to a crime. Inthis way, the user of the mobile computing device may determine that theat least one other user was in proximity to the crime. As such, the userof the mobile computing device may determine that if the at least oneother user is proximate to the particular crime, then the informationprovided by the at least one other user about the crime may be moreaccurate, truthful, credible, or otherwise useful in characterizing ordescribing the crime.

In the example of FIG. 1 , user application 128B may output for displaya user interface 132. User interface 132 is one example of a userinterface that may provide functionality in accordance with techniquesof this disclosure; however, other arrangements of the content of userinterface 132 are possible. Although user interface 132 includes certaincontent in FIG. 1 for example purposes, additional content may beincluded in the user interface and in other examples only a subset ofcontent shown in user interface 132 of FIG. 1 may be included. In someexamples, the appearance of content may be different that in FIG. 1although such content may provide equivalent or similar functionality.For instance, an indication that a user's computing device is proximateto a crime may be represented in any number of ways, the example of FIG.1 being an example of such an indication.

User interface 132 illustrates a discussion view of a particular crime.That is, user interface 132 may include information that describes aparticular crime and one or more discussion messages from users thatprovide information about the particular crime. For instance, userinterface 132 includes crime element 134, and a set of one or morediscussion elements 136A-136B (“discussion elements 136”) which may bepresented in any suitable way such as a list in FIG. 1 . Any number ofdiscussion elements 136 may be associated with a particular crime, andcorrespond to information submitted by users about the particular crime.As described in this disclosure, users may submit information (e.g.,tips, comments, or any other content) about a crime that are descriptiveof it, and such that the user is anonymous to other users and serverapplication 130. In this way, system 100, using anonymization network120 and user interface 132, may enable a user to provide informationthat the user would otherwise not feel safe sharing if user could beidentified. Moreover, by providing a collaborative or social interfacein which information about a particular crime is discussed (and withproximity information as further described herein), more information maybe submitted by users which can be used to solve the particular crime,discourage future crimes, and/or improve the safety of the neighborhoodor region around the crime.

As described above, user interface 132 includes crime element 134, whichmay be implemented as a graphical user interface element, such as a cardthat includes text, images or other suitable content. Crime element 134(and discussion elements 136) may be based on data sent by serverapplication 130 to user application 128B. For instance, serverapplication 130 may receive an indication of user input to select thecrime that corresponds to crime element 134. Server application 130 maysend crime information that is populated by user application 128B intocrime element 134. Server application 134 may also send discussioninformation that is populated by user application 128B into discussionelements 136.

Crime element 134 includes crime type 138 (e.g., “Assault”) for theparticular crime in the discussion view. Any number of crime types arepossible including but not limited to: Arrest, Arson, Assault, Robbery,Shooting, Theft, Vandalism, People Trafficking, Drugs, Terrorism, MassGathering, Riot, or any other indication of a crime or event. Crimeelement 134 may include a law enforcement sponsor indicator (LESI) 140.LESI 140 may be a flag or other indicator that indicates a lawenforcement agency or other source of authority has sponsored the crimein the discussion view. The source of authority may provide anindication of user input to server application 130 to indicate it issponsoring the crime. By sponsoring the crime in the discussion view,the source of authority may evaluate the quality, usefulness, and/orvalue of discussion information provided by users and release aremittance for the crime (further described herein) to one or moreusers. For instance, if a source of authority determines that theinformation provided by a particular user was essential, helpful, oruseful to solving a crime, the source of authority may release theremittance for the crime to the particular user in accordance withtechniques of this disclosure.

Crime element 134 may include crime details 142. Crime details 142 maybe any details descriptive of the particular crime in the discussionview of user interface 132. Crime details 142 may include but are notlimited to: date of crime, time of crime, street address of crime, cityof crime, state of crime, zip code of crime, neighborhood of crime,season of crime, or any other details that describe the crime in thediscussion view. In some examples, crime element 134 may includediscussion activity indicator 144. Discussion indicator 144 may indicatea level of discussion activity, for example over a period of time, for aparticular crime. In some examples, the level of discussion activity maybe the number of discussion messages generated by users over a period oftime. In this respective, discussion indicator 144 may indicate avelocity of discussion messages generated by users, which may indicate alevel of interest in a particular crime. In the example of FIG. 1 ,three chat bubble icons may have different respective sizes and one ofthe three chat bubble icons may be visually indicated as “active” (e.g.,by color, opacity or any other visual indication) and the other two chatbubble icons may be indicated as “inactive”. In the example of FIG. 1 ,the level of discussion activity is moderate as indicated by themiddle-sized chat icon which is “active”, while the “low” and “high”discussion activity chat icons are indicated as “inactive”. Serverapplication 130 may send data for each crime that indicates the level ofdiscussion activity for the crime, which user application 128B may useto indicate which discussion activity chat icon is active and whichothers are inactive. Alternatively, other indicators of the level ofdiscussion activity for a crime may be used, such as but not limited to:color, size, different icon appearance(s), or any other visualindication.

Crime element 134 may include bounty amount 147. As described in thisdisclosure, system 100 provides an anonymity platform for users toreceive incognito remittances for information that improves the safetyof a community. By providing techniques for anonymous communication andprovisioning of incognito remittances for particularized crimes, system100 enables the collection, dissemination, and compensation ofinformation for solving particular crimes, discouraging future crimes,and/or improving the safety of the neighborhood or region around thecrime. In this way, the integration of anonymization network 120 withuser proximities to crimes and incognito payments for such users thatprovide valuable information relating to such crimes provides a systemthat enables the collection and use of such information that otherwisecould not be obtained, shared, or used by anonymous users and sources ofsources of authority to solve particular crimes, discourage futurecrimes, and/or improve the safety of the neighborhood or region aroundthe crime.

Techniques of this disclosure enable one or more users to submit andassociated a bounty for a crime. A bounty may be a sum of money or othercompensation provided in exchange for information about a particularcrime or particular event. The bounty may later be released as aremittance in response to a user input as an incognito remittance thatis received by one or more users who have provided information relatingto the particular crime or particular event. As described in thisdisclosure, to associate a bounty with a crime, user application 128Bmay output a bounty submit icon in a graphical user interface.

In FIG. 1 , in response to a user input that selects bounty submit icon149, user application 128B may output for display one or more userinterfaces in which a user may submit payment information and/or abounty amount for a particular crime. The payment information mayindicate payment account information for a payment account of the user,such as a credit card account, bank account, blockchain payment account(e.g., BitCoin, Ethereum, etc.), online payment account (e.g., PayPal,Stripe, etc.), or any other type of payment account. The paymentinformation may also include an amount (e.g., denominated in aparticular current) of the bounty that the user assigns to theparticular crime. The user may provide a user input that causes userapplication 128B to send the payment information to server application130. Server application 130 may store data that associates the amount ofthe bounty with the crime. Server application 130 may send a message topayment server 126, which may cause a transfer of money or othercompensation from a payment account of user 108B to a payment accountassociated with a service provider operating server application 130. Forinstance, the message may specify an account of user 108B, an account ofthe service provider operating server application 130, and/or a bountyamount for a particular crime. Payment server 126, which may representone or more computing devices, may execute one or more transactionsbased on the message to transfer the money or other compensation from anaccount of user 108B to an account of the service provider operatingserver application 130. As described in this disclosure, the money orother compensation in the account of service provider operating serverapplication 130 may be released and provided as an incognito remittanceto one or more other users that provide information relating to thecrime. In the example of FIG. 1 , a user has provided $5,000 as a bounty147 for the crime indicated by crime element 134. In some examples,bounty 147 indicates a sum of bounties from multiple different usersthat have provided money or other compensation in association with thecrime for crime element 134.

As described herein, server application 130 may select an accountidentifier of the user. Server application 130 may generate a messagethat includes the account identifier of the user, an account identifierof an account controlled by at least one of user 102B or an operator ofa service provided by the at least one server computing device, and anamount of the remittance. In some examples, server application 130 maysend the message to at least one remote computing device (e.g., paymentserver 126) that executes a transaction that transfers at least aportion of the amount of the remittance from the account controlled byat least one of user 102B or the operator of server application 130 toan account associated with the account identifier of the user. In someexamples, a portion of the amount of the remittance is denominated in acryptocurrency and the account associated with the account identifier ofthe user is denominated in the cryptocurrency. In some examples, the atleast one server computing device of data center 114, to perform atleast one operation that provides the remittance to the user, determinesa portion (e.g., fee) of the remittance amount based at least in part onthe total amount of the remittance. The at least one server computingdevice may generate an amount of the remittance provided to a user basedon the portion representing the fee. For instance the user may receive aremittance equal to the total remittance less a fee.

Crime element 134 may also include a favorite icon 151, which mayindicate whether a user has flagged or specified the crime as a“favorite” or otherwise particular interest. Server application maystore the indication that a crime is a favorite of a user, such that auser application may receive such favorite information in order tofilter or otherwise sort crimes based on the favorite indication.

As described herein, server application 130, based at least in part ondetermining that a location from a set of locations of one of mobilecomputing devices is within a threshold distance of a location of acrime, generates a proximity indication that a user associated with theone of the mobile computing devices is proximate to the crime. In theexample of FIG. 1 , server application may include one or more thresholddistances, such as threshold distances 152A and 152B. In some examples,the threshold distances may be hard-coded, user-defined, and/ormachine-generated. Server application 130 may determine that a locationof computing device 128A was within threshold distance 152A from alocation of crime 112, and a time difference between the timestamp ofthe location of computing device 128A and timestamp of the location ofcrime 112 is less than a threshold time. Accordingly, server application130 may generate a proximity indication that user 128A is proximate tocrime 112.

A proximity indication may be any data that indicates a user isproximate to a crime. For instance a proximity indication may be anenumerated value, such as “close”, “moderate”, “far” or any othersuitable enumerated value. In the example of FIG. 1 , server application130 may associate “close” proximity indication with a user, for aparticular crime, that is within threshold distance 152A of crime 112,“moderate” proximity indication with a user that is within thresholddistance 152B but outside of threshold distance 152A, and “far”proximity indication with a user that is outside of threshold distance152B. In other examples, proximity indication may be a set of numericalvalues, which may be scores, distances, or any other values thatindicate a distance relationship between a user and a crime. In someexamples, a proximity indication may be one or more values that userapplication may use to indicate a distance relationship between a userand a crime. The proximity indication may indicate a degree or amount ofphysical distance between the user and the crime. The proximityindication may indicate a degree or amount of temporal distance betweenthe timestamp of the crime and the timestamp of a user's locationrelative to the crime. As shown in FIG. 1 , the user interface maycontemporaneously include the descriptive data in association with theproximity indication and an amount of the remittance.

Server application 130, when sending discussion information to, forexample, user application 128B, may associate a proximity indicationwith each discussion message generated by a user that is represented bya discussion element in user interface 132. For instance, user 108A mayhave been at a location within distance threshold 152A of crime 112 andwithin a time threshold of the timestamps of crime 112 and the timestampof the location of user 108A. User 108A may have submitted discussioninformation via a user interface provided by user application 128A thatis descriptive of crime 112. The discussion information may be text,images, videos, audio data, hyperlinks, or any other informationdescriptive of the crime. In the example of FIG. 1 , discussioninformation 147 of discussion element 136A is text “The truck was redwith license plate HTY-687 and is usually parked at 109643 New CastleRd.”

Discussion element 136A may also include proximity element 148.Proximity element 148 may be based on a proximity indication receivedfrom server application 130. For instance, the discussion messagerepresented by discussion element 136A may be based on discussioninformation submitted by user 108A. The proximity indication mayindicate that user 108A was proximate to (e.g., within distancethreshold 152A of) crime 112. As shown in FIG. 1 , proximity element 148includes multiple concentric circles. Each concentric circle mayrepresent whether a use is within a threshold distance of a crime. Sinceuser 108A was within distance threshold 152A of crime 112, the innermostconcentric circle corresponding to distance threshold 152A may bevisually differentiated from the other concentric circles representingother distance thresholds. Visual differentiation of different distancethresholds may be indicated in any number of ways including color,opacity, size, texture or pattern, or any other visual differentiator.Although illustrated as concentric circles in FIG. 1 , any other visualrepresentation may be used, such as bars, lines, images, colors, or anyother suitable visual differentiator that differentiates differentdistance thresholds.

Discussion element 136A may also user identification elements 150 thatidentify a user that submitted the discussion information. For instance,user identification element 150A is the user identifier of user 108A anduser identification element 150B may be an image that corresponds touser 108A, such as an avatar or other image, which may be user-submittedor system generated. In some examples, discussion element 136A mayinclude time information 152 that indicates when the discussioninformation was submitted by user 108A. Example time information mayinclude time elapsed since discussion information was submitted toserver application 130, time when discussion information was submittedto server application 130, and date when discussion information wassubmitted to server application 130.

Discussion element 136A may include discussion message scores 156A,156B. Users may select discussion message score controls 154A or 154B toincrement or decrement, respective, discussion message scores 156A,156B. Discussion message scores 156A, 156B respective indicate positiveand negative discussion message scores for the discussion informationincluded in discussion element 136A. By enabling users to selectdiscussion message score controls 154A or 154B, users may rank oridentify discussion information that more accurately, relevant, and/oruseful to solve the particular crime, discourage future crimes, and/orimprove the safety of the neighborhood or region around the crime. Userapplication 128B may receive discussion message scores 156A, 156B fromapplication server 130 and may send indications of user input whendiscussion message score controls 154A or 154B are selected by user108B. Server application 130 may send and receive discussion messagescores to and from user applications 128.

Discussion element 136A may include reply element 157. Discussionelements 136 may include one or more threads nested below each parentdiscussion element. For instance discussion element 136A may be a parentdiscussion element and one or more users may reply to discussion element136A, which may create one or more child discussion elements. To replyto discussion element 136A, a user may provide a user input to selectreply element 157. User application 128A may update user interface 132to display an input control in which a user can provide discussioninformation, which may be displayed in a child discussion element. Insome examples, discussion element 136A may include a new discussionmessage element (not shown) that when selected updates user interface134 to enable a user to input discussion information for inclusion in anew parent discussion element. In this way, users may reply todiscussion information in parent discussion elements and/or childdiscussion elements.

In the example of FIG. 1 , user 108B may be a source of authority (e.g.,law enforcement agency, government agency, or other entity of the publictrust), although in other examples user 108B may not be a source ofauthority. User 108B may determine that discussion information 147provided by user 108A was essential, helpful, or useful to solving crime112. Accordingly, user 108B may provide an indication of user input todisplay a release user interface (not shown) for releasing or providinga remittance to user 102A that corresponds to the bounty for crime 112.In some examples, the release user interface (e.g., in FIG. 13 ) mayenable user 108B to distribute the total amount of the bounty to one ormore users as one or more remittance. In the example of FIG. 1 , user108B may provide an indication of user input that releases 100% of the$5,000 bounty as a remittance to user 102A for discussion information147.

To release the $5,000 bounty as a remittance to user 102A, userapplication 128B sends a message to server application 130 thatindicates one or more of: a user identifier of user 108B, an indicationto release a remittance to user 108A, a proportion or percentage of thebounty that will be released as a remittance to user 108A, and anidentifier of the crime and/or bounty, and any other suitableinformation for providing the remittance to user 108A. Serverapplication 130 may receive the message.

In some examples, if server application 130 determines that user 108Ahas payment information for an account for receiving payment stored atserver application 130, server application 130 sends a message topayment server 126, which may cause a transfer of money or othercompensation from a payment account of the service provider operatingserver application 130 to a payment account associated with user 108A.For instance, the message may specify an account of user 108A, anaccount of the service provider operating server application 130, and/ora remittance amount. Payment server 126, which may represent one or morecomputing devices, may execute one or more transactions based on themessage to transfer the money or other compensation from an account ofthe service provider operating server application 130 to the account ofuser 108A. As described in this disclosure, the money or othercompensation in the account of service provider operating serverapplication 130 may be released and provided as an incognito remittance(or non-incognito remittance) to one or more other users that provideinformation relating to the crime. In the example of FIG. 1 , user 108Areceives a $5,000 remittance for providing discussion information 147for crime 112. In this way, server application 130, in response toreceiving, using anonymization network 120, descriptive data generatedby user 108A that is descriptive of crime 112, sends the descriptivedata to other mobile computing devices such as 110B that is associatedwith user 108B, and provides the remittance to user 108A in response toreceiving, from mobile computing device 110A that outputs a userinterface in which the descriptive data (e.g., discussion information147) is associated with proximity indication (e.g., proximity element148 based on a proximity indication), an indication to release theremittance provided by user 108B.

As described in FIG. 1 and throughout this disclosure, server computingdevices 116 may include or use one or more components residing in and/orexecuting on server computing devices 116 or at one or more other remotecomputing devices (e.g., mobile computing devices 110) to perform theoperations and provide the functionality described in this disclosurewith respect to server computing devices 116. Mobile computing devices110 may include or use one or more components residing in and/orexecuting on mobile computing devices 110 or at one or more other remotecomputing devices (e.g., server computing devices 116) to perform theoperations and provide the functionality described in this disclosurewith respect to mobile computing devices 110. Accordingly, variousfunctionality described in some examples as performed by servercomputing devices 116 may in other examples be implemented at mobilecomputing devices 110, and various functionality described in someexamples as performed by mobile computing devices 110 may in otherexamples be implemented at server computing devices 116. For instance,mobile computing device 110A may determine a set of locations of mobilecomputing device 110A. Mobile computing device 110A may determine that alocation from the set of locations of mobile computing device 110A iswithin a threshold distance of a location of an event. Based on thedetermination that the location from the set of locations of mobilecomputing device 110A is within a threshold distance of the location ofthe event, mobile computing device 110A may generate a proximityindication. The proximity indication may indicate that user 108A isproximate to the event. Mobile computing device 110A may send theproximity indication to one or more of server computing devices 116.Server 116 may process or otherwise use the proximity indication asdescribed in this disclosure. In some examples, mobile computing device110A may send the proximity indication to one or more of servercomputing devices 116, but mobile computing device 110A may refrain fromsending the set of locations of mobile computing device 110A to one ormore of server computing devices 116. In some examples, devices maycommunicate data with one another to implement the various functionalityof components described in this disclosure. Further techniques aredescribed with respect to the following figures.

FIG. 2 is a block diagram illustrating further details of a servercomputing device shown in FIG. 1 , in accordance with one or moreaspects of the present disclosure. Server computing device 200 is anexample of server computing device 116A, as illustrated and described inFIG. 1 . FIG. 2 illustrates only one particular example of servercomputing device 200, and many other examples of server computing device200 may be used in other instances and may include a subset of thecomponents included in example server computing device 200 or mayinclude additional components not shown in FIG. 2 . In some examples,multiple instances of server computing device 200 may interoperatetogether, such as in a data center or distributed computing environment,to provide the functionality of server computing device 200 described inthis disclosure.

As shown in the example of FIG. 2 , server computing device 200 includesuser component 226, discussion component 228, crime component 230,interface component 232, prediction component 234, bounty component 236,proximity component 238, obfuscator component 240, user data 242, crimedata 244, bounty data 246, discussion data 248, location data 250,operating system 218, one or more storage components 202, one or moreinput components 204, one or more communication components 206, one ormore output components 208, one or more processors 210, and one or morecommunication channels 211.

Communication channels 211 may interconnect one or more devices and/orcomponents of server computing device 200 for inter-componentcommunications (physically, communicatively, and/or operatively). Insome examples, communication channels 211 may include a system bus, anetwork connection, an inter-process communication data structure, orany other method for communicating data.

One or more input components 204 of server computing device 200 maygenerate or receive data indicating input from one or more humans and/ordevices. Example types of input include tactile, audio, and visualinput, although any suitable types of input may be generated or receivedby input components 204. In one example, input components 204 include apresence-sensitive display, touch-sensitive screen, mouse, keyboard,voice responsive system, video camera, microphone, or any other type ofdevice for detecting input from a human or device.

One or more output components 208 of server computing device 200 maygenerate output. Examples of output are tactile, audio, and videooutput. Output components 208 of server computing device 200 may includea presence-sensitive display, sound card, video graphics adapter card,speaker, cathode ray tube (CRT) monitor, liquid crystal display (LCD),or any other type of device for generating output to a human or machine.

One or more communication components 206 may allow server computingdevice 200 to communicate with external devices and/or systems. In someexamples, communication may be via one or more wired and/or wirelessnetworks, via one or more communication channels that do not include anetwork, and/or a combination of such networks and communicationchannels. Communication components 206 may transmit and/or receivenetwork signals being transmitted and received other devices and/orsystems connected to one or more networks. Examples of communicationcomponents 206 include network interface cards (e.g. such as an Ethernetcard), optical transceivers, radio frequency transceivers, GPSreceivers, or any other type of device that can send and/or receiveinformation. Other examples of communication components 208 may includelong and short wave radios, cellular data radios, wireless networkradios, as well as universal serial bus (USB) controllers, Bluetoothcontrollers and any other suitable components for communication.

One or more storage components 202 of server computing device 200 maystore information or instructions that server computing device 200processes during operation of server computing device 200. For example,storage components 202 may store data that modules or components mayaccess during execution at server computing device 200. In someexamples, storage components 202 are temporary memories, meaning that aprimary purpose of storage components 202 is not long-term storage.

Storage components 202 may be configured for short-term storage ofinformation as volatile memory and therefore not retain stored contentsif powered off. Examples of volatile memories include random accessmemories (RAM), dynamic random access memories (DRAM), static randomaccess memories (SRAM), and other forms of volatile memories known inthe art.

Storage components 202 may be configured to store larger amounts ofinformation than volatile memory and may further be configured forlong-term storage of information as non-volatile memory space and retaininformation after power on/off cycles. Examples of non-volatile memoriesinclude magnetic hard discs, optical discs, floppy discs, flashmemories, or forms of electrically programmable memories (EPROM) orelectrically erasable and programmable (EEPROM) memories.

Storage components 202, in some examples, include one or morecomputer-readable storage media. In some examples, storage components202 represent non-transitory computer readable storage medium that storeinstructions later executed by one or more processors 210 duringoperation of server computing device 200. For example, storagecomponents 202 may store program instructions and/or information (e.g.,data) associated with components included application layer 216 ofserver computing device 200. Application layer 216 may include one ormore applications such as server application 217, which may be anexample of server application 130 in FIG. 1 . Server application 217 mayinclude logic tier 222 with one or more components that perform one ormore operations and data tier 224 with one or more datastores or otherconfigurations of data.

One or more processors 210 may implement functionality and/or executeinstructions within server computing device 200. For example, processors210 on server computing device 200 may receive and execute instructionsstored by storage components 202 that execute the functionality ofcomponents included in application layer 216. The instructions executedby processors 210 may cause server computing device 200 toread/write/etc. data that is stored within storage components 202.Processors 210 may execute instructions of components included inapplication layer 216 to cause server computing device 200 to performthe operations described in this disclosure. That is, components inapplication layer 216 may be operable by processors 210 to performvarious operations, actions, and/or functions of server computing device200 in accordance with one or more aspects of the present disclosure.

As shown in FIG. 2 , server computing device 200 includes user component226. User component 226 may receive one or more types of information viaanonymization network 120 from a user application (e.g., userapplication 128B), which user component 226 may use to generate a uniqueuser identifier for user 108B, which is stored in user data 242 and usedby server application 217 in accordance with techniques of thisdisclosure. As described in FIG. 1 , the one or more types ofinformation received by user component 226 do not personally identifyand cannot personally identify mobile computing device 110B, userapplication 128B or user 108B. For instance, the one or more types ofinformation may be a random number, a timestamp, a hash value, or anyother type of information. User component 226 may apply one or morefunctions or other operations to the one or more types of informationreceived from mobile computing device 128B to generate a user identifierfor user 108B. For instance, user component 226 may apply a hashfunction, random number generation function, or any other function tothe one or more types of information to generate the user identifier foruser 108B. The user identifier may be stored by user component 226 inuser data 242. Accordingly, user component 226 may generate, store, anduse the unique user identifier that is associated with user 108B, useapplication 128B, and/or mobile computing device 110B for purposes ofdistinguishing between different unique users and/or devices, but cannotbe used to personally identify or physically locate user 108B, userapplication 128B, and/or mobile computing device 110B. In this way, usercomponent 226 may maintain identifiers for different unique users and/ormobile computing device without maintaining information that can be usedto personally identify and/or physically locate users or mobilecomputing devices that use services provided by server application 217.

Server application 217 may include discussion component 228. Discussioncomponent 228 may receive requests from user applications to storediscussion information generated by users into discussion data 248.Discussion data 248 may include discussion information such as text,images, videos, audio data, or any other information descriptive of acrime. In some examples, discussion data 248 includes relationshipsbetween parent and child discussion messages. Discussion component 228may provide to a user application a set of one or more discussionmessages with discussion information stored in discussion data 248 for acrime. The discussion information may be output for display indiscussion elements as shown in FIG. 1 . The discussion messages mayinclude but are not limited to proximity indications, discussion messagescores, and other metadata about the discussion messages such as dateand time information, author information for the discussion informationand any other suitable information.

Server application 217 may include crime component 230. Crime component230 may receive crime data 244 from one or more other computing devicesand/or otherwise store crime data 244. In some examples, crime component230 may send crime data 244 to one or more mobile computing devices.Crime component 230 may include proximity component 238. Proximitycomponent 238 may determine a set of respective distances between eachcrime of a set of crimes and each instance of location data from a setof location data. For example, proximity component 238 may determine aset of respective distances between each crime of a set of crimes andeach instance of location data 250 from a set of location data that wassent by a user application to server application 217. Server application217 may determine the respective distances for those instances oflocation data 250 having timestamps which, when compared to thetimestamps of respective crimes in the set of crimes, have a timeduration that is less than or equal to a time threshold. Proximitycomponent 238 may determine respective distances for those instances oflocation data 250 having timestamps which, when compared to thetimestamps of respective crimes in the set of crimes, are less than athreshold time between the timestamp of respective crime and therespective instance of location data. In this way, proximity component238 may determine the respective distances between a user mobilecomputing device and crime when the mobile computing device wastemporally proximate to a crime.

Server application 217 may include interface component 232. In someexamples, interface component 232 may provide one or more endpoints thatprovide data to other computing devices such as mobile computingdevices. For instance, interface component 232 may provide one or moreRepresentation State Transfer (REST) interfaces or “endpoints” whichmobile application may call to send and/or receive information with oneor more components of logic dirt 222.

Server application 217 may include prediction component 234. Predictioncomponent is further described in FIG. 4 . In some examples, predictioncomponent 234 may receive a crime profile that includes a set ofvariables that describe or otherwise characterize a particular crime.Prediction component 234 may generate a bounty profile, which mayindicate a bounty amount, bounty time, and/or other characteristics of abounty, where the bounty profile has a likelihood or score thatsatisfies a likelihood threshold, and the likelihood threshold indicatesthat the bounty profile, if applied to the crime, will produceinformation from one or more users that solves the particular crime,discourages future crime, and/or improves the safety of the neighborhoodor region around the crime.

Server application 217 may include obfuscator component 240. Obfuscatorcomponent 240 may reduce or prevent doxing of individuals in textprovided to server application 217, such as in a discussion message,crime data, or any other information. In some examples, doxing may meanbroadcasting private or identifiable information (especially personallyidentifiable information) about an individual or organization in apublicly viewable way. Obfuscator component 240 may implement one ormore techniques to reduce or prevent doxing of individuals.

As described herein, obfuscator component 240 may determine whether, forexample, text in a discussion message, includes private or identifiableinformation about an individual or organization that may dox theindividual. As an example, obfuscator component 240 may perform a lookupof text submitted by a user against a set of words that represent personnames, although any set of words may be used. In some examples,obfuscator component 240 may determine a likelihood or score that text(e.g., a word or set of words) includes private or identifiableinformation about an individual or organization that may dox theindividual, and if the likelihood or score satisfies a threshold (e.g.,greater than or equal to), then obfuscator component 240 may determinethat the text includes private or identifiable information about anindividual or organization that may dox the individual.

In some examples, if obfuscator component 240 determines that the textincludes private or identifiable information about an individual ororganization that may dox the individual, obfuscator component 240 mayassociate a label with the word (e.g., name), such that when displayedat a mobile computing device, the text with the label is obfuscatedusing one or more techniques. Such techniques may include obfuscatingeach vowel, every n-th character of the word, or the entire word to nameonly a few examples. In some examples, anti-doxing techniques may beapplied to images, audio, and/or video content uploaded by users aswell. In some examples, natural language processing may be appliedagainst user submitted text to determine whether user submitted text ismaking an allegation against a particular person or not making anallegation against a particular person. If an allegation is detected,then obfuscator component 240 may obfuscate text, audio, (e.g.,obfuscate the sound), and/or images or video (e.g., obfuscate the visualcontent).

Obfuscator component 240 may implement one or more natural languageprocessing techniques, such as sentiment analysis and named entityextraction either alone or in combination, to identify a named entity(e.g., a person) and determine whether the named entity is characterizedby an accusatory or negative modifier, such that the combination ofnamed entity and modifier would constitute defamation of the namedentity. In some examples, obfuscator component 240 may generate aconfidence score or probability that the a portion of content wouldconstitute defamation of the named entity, based at least in part onwhether the named entity is characterized by an accusatory or negativemodifier. Example techniques which may be implemented by obfuscatorcomponent 240 include, but are not limited to the following, each ofwhich is hereby incorporated by reference herein in its entirety: TheDetection and Analysis of Bi-polar Phrases and Polarity Conflicts,http://www.zora.uzh.ch/id/eprint/99629/1/n1pcs2014.pdf, (2014); APattern Dictionary for Natural Language Processing,https://www.cairn.info/revue-francaise-de-linguistique-appliquee-2005-2-page-63.htm(2005); Sentiment analysis: capturing favorability using naturallanguage processing,https://pdfs.semanticscholar.org/cOed/c993eaaM50b3d599e7f7e11187dc4c76c1.pdf(2003); The Stanford CoreNLP Natural Language Processing Toolkit,https://nlp.stanford.edu/pubs/StanfordCoreNlp2014.pdf (2014); Techniquesand Applications for Sentiment Analysis,https://cacm.acm.org/magazines/2013/4/162501-techniques-and-applications-for-sentiment-analysis/abstract(2013).

In some examples, obfuscator component 240 may identify, based at leastin part on application of natural language processing to descriptivedata, an accusation in a semantic meaning of the descriptive data. Insome examples, an accusation may be a charge or claim that someone hasdone something. Examples of an accusation may include a charge or claimthat a person committed an act, made a statement, or was associated withsome event, to name only a few examples of accusations. In someexamples, the charge or claim may associate the person with a wrongdoingor other undesirable act. Obfuscator component 240 may, in response toidentification of the accusation, identify at least a portion of contentin the descriptive data that corresponds to the accusation. Forinstance, using sentiment analysis, obfuscator component 240 maydetermine the sentiment of a set of text is an accusation or negativeconnotation, and using named entity extraction may determine that theaccusation or negative connotation corresponds to, for example, a propernoun, name, or other identifier that was accused or disparaged.Obfuscator component 240 may perform at least one operation to obfuscateat least the portion of the content in the descriptive data. Forinstance, obfuscator component 240 may generate data that associates alabel with the descriptive data or at least a portion of content in thedescriptive data. In some examples obfuscator component 240 may modifyat least the portion of the content in the descriptive data to change atleast one of a character, pixel value, or sound of the descriptive data.For instance, obfuscator component 240 may select an area of interest inan image or video and alter the pixels to blur or otherwise obfuscatethe area of interest (e.g., a face of person or other identifyingfeature). In some examples, obfuscator component 240 may select an areaof interest in a sound recording and alter the sound values within thearea of interest such that the sound in the area of interest isunintelligible. In some examples, obfuscator component 240 may identifyan area of interest in text, such as a person name, address, telephonenumber, email address, or any other identifying information andobfuscate such text.

As described herein, in some examples data may be obfuscated for certaintypes or roles of users but not obfuscated or other types or roles ofusers. In some examples data may be obfuscated in certain types of userinterfaces, e.g., user interface 900, but may not be obfuscated in otheruser interfaces, e.g., user interface 1200. In some examples, data maybe obfuscated for users of one type or role in a user interface, but thedata may not be obfuscated for users of a different type or role in thesame user interface.

In some examples, a label may not be associated with the word (e.g.,stored as metadata with the word), but the word or set of words may beobfuscated by obfuscator component 240 and stored as an obfuscated wordin, e.g., discussion data 248. In some examples, certain user types orroles may be able to view non-obfuscated words that are obfuscated for adifferent types or roles. For examples, a special user (e.g., source ofauthority or law enforcement) may be assigned a user type or role inuser data 242 with the user identifier that permits the source ofauthority user to view non-obfuscated words that are obfuscated for adifferent types or roles, while a non-special user may not view theobfuscated words. A user application executing at a mobile device asdescribed in this disclosure may receive, from server application 217,obfuscated words based on different types or roles, or the userapplication may determine based on a label associated with a words thatuser application will obfuscate the word before it is displayed in theuser interface. In some examples, obfuscator component 240 may encryptor otherwise encode obfuscated words or text (e.g., with a key in someexamples), such that only certain user types or roles using a userapplication may decrypt or decode the obfuscated words or text to viewthe non-obfuscated words or text. In any case, obfuscator component 240may implement one or more techniques to prevent or limit viewing ofprivate or identifiable information about an individual or organizationthat may dox the individual, which may have been submitted by one ormore users of server application 217.

In some examples, bounty component 236 may charge a fee on a bounty thatis released. For example, bounty component 236 may reduce the amount ofpayment released to a particular user by deducting a fee, which may be apercentage or a fixed amount. An accounting of the fee may be stored inbounty data 246. In some examples, each fee may be variable based on oneor more factors that are determined by bounty component 236. Examplefactors may be bounty amount, number of users receiving a proportion ofthe bounty, crime type, or any other metric or characteristic describedin this disclosure. In some examples, bounty component 236 may charge afee for each bounty and/or crime/event that is posted or otherwisecreated. In some examples, the fee that is changed in any case may bebased at least in part on the type or role of the posting user.

In some examples, to protect the anonymity of a user, bounty component236 may automatically delete information that indicates a release of aremittance to a user after the remittance has been transfer to the user.For instance, in response to a remittance being selected for release toa user, bounty component 236 may store data that defines an associationbetween a transaction identifier, an identifier of user that willreceive the remittance, and an amount of the remittance. In someexamples, bounty component 236, in response to the remittance beingtransferred to an account of the user and from an account controlled byan operator of a service provided by the at least one server computingdevice, may automatically destroy the data that defines the associationbetween the transaction identifier, the identifier of user, and theamount of the remittance, such that the data that defines theassociation cannot be reconstructed. Any suitable techniques known inthe art may be used to destroy the data such that the data that definesthe association cannot be reconstructed.

In some examples, bounty component 236 may release a remittance to auser as a set of sub-remittances. For instance, bounty component 236 maydivide a remittance into a two or more smaller sub-remittances which arereleased to a user in separate transactions. The two or more smallersub-remittances may be amounts that cumulatively sum to an amount equalto the remittance. In some examples, the number of and/or size of thesub-remittances may be randomized or otherwise determined based on oneor more pre-configured rules. In some examples, the sub-remittances maybe released at different dates and/or times, which may be randomized orotherwise determined based on one or more pre-configured rules. In someexamples, the sub-remittances may be released using one or more paymentprocessing services associated with one or more accounts of the userreceiving the remittance.

In some examples, any user may create a crime or other event that isstored in crime data 244. For instance, mobile computing device 110B mayoutput for display a graphical user interface in which a user may definedetails about a crime, event, or other occurrence. Mobile computingdevice 110B may send the data to server computing device 200. Crimecomponent 230 may store the details of the crime, event or otheroccurrence in crime data 244. In some examples, when crimes, events, oroccurrences are output for display at other mobile computing devices ofusers, the crime, event, or other occurrence and its details may beoutput for display in a manner that is the same or similar as describedwith respect to crimes in FIG. 1 .

In some examples, a source of authority may not sponsor a bounty. Insuch examples, a first user may initially create a crime, event, orother occurrence that is stored in crime data 244. The first user mayassociate a remittance with the crime, event, or other occurrence, whichis stored in bounty data 246. Bounty component 236 may transfer theamount of the remittance from an account of the first user to an accountof an operator of server application 217. A second user may, in responseto viewing information about the crime, event, or occurrence, may submitdescriptive data that the first user determines to be relevant to thecrime, event, or occurrence. In some examples, the first user mayprovide a user input that causes bounty component 236 to release theremittance to the second user, as described in this disclosure. In someexamples, the second user may provide an indication of user input thatrates the first user, which is stored in one or more of user data 242and/or bounty data 246. For instance, a rating may include a range ofnumeric or discrete values from low to high. If the first user does notrelease the remittance or releases a portion of the remittance that ineither case is unsatisfactory to the second user for the quality ofinformation provided, then the second user may provide a correspondingrating. In some examples, the first user may also rate the second user.

In some examples, the remittance may not be paid immediately to thesecond user or returned to the first user. If, for example, the seconduser provides a rating of the first user below a threshold rating foreither a portion of remittance released to the second user or theremittance not being released at all (although the second user providedinformation), then the remittance may be temporarily maintained in anaccount controlled by the operator of server application 217. In someexamples, the second user may provide feedback or explanation to theoperator of server application 217 for the basis of the rating (e.g.,the information provided by the second user was determined or validatedto have been relevant, useful, valuable in response to the crime, event,or occurrence described by the first user). In some examples, theoperator of server application 217 may release a portion of theremittance to the second user based on an evaluation of the informationprovided, remittance amount, or any other relevant information. In someexamples, the operator of server application 217 may release a firstportion back to the first user, a second portion to the second user,and/or a third portion of the remittance may be retained by the operatorof server application 217.

In some examples, a remittance submitted as a bounty by a user mayincrease in amount over time. For instance, a user may authorize aninitial bounty amount and a maximum bounty amount that is larger thanthe initial bounty amount. The user may specify a time duration for thebounty to remain active in association with a crime, event, oroccurrence, such that when active the crime, event, or occurrence isviewable on a map. In some examples, the bounty amount may increaselinearly or non-linearly over the time duration to the maximum bountyamount. Once the maximum bounty amount is reached or at some definedtime after the maximum bounty amount is reach, the crime, event, oroccurrence may be removed or changed to inactive, such that it is nolonger viewable by users.

In some examples, server computing device 200 may include targetedcontent component 241. Targeted content component 241 may generateand/or send targeted content to user applications for display on mobilecomputing devices. Targeted content may include, but are not limited to:offers, rewards, political information, entertainment information,sports information, advertisements, discounts, public interestinformation, or other informational content. In some examples, targetedcontent component 241 may generate targeted content based on targetrelevance data. Target relevance data may be any data that increases,improves, or otherwise affects the relevance of targeted content to auser or group of users. For instance, target relevance data may include,but is not limited to: user data 242 (including demographicinformation), crime data 244, bounty data 246, discussion data 248, andlocation data 250. Other examples of target relevance data may includebut are not limited to: proximity indications; data from externalsources such as events, news, neighborhood information, weather, crimeinformation, demographic population data, schedules, purchasingpreferences, purchasing ability, geographic information, businessinformation; date and/or time; and any results or outputs generated byany components of server computing device 200 and/or mobile computingdevice 300 in FIG. 3 .

In some examples, to generate targeted content, targeted contentcomponent 241 may select a set of one or more instances of targetrelevance data. Targeted content component 241 may select the one ormore instances of target relevance data based one or more criteria. Suchcriteria may include but are not limited to user identifier, userlocations and/or proximity indications associated with a user,descriptive data generated by a user, event locations within a thresholddistance or otherwise proximity to a user, event descriptions, or anyother criteria that may be used to select target relevance data.Targeted content component 241 may determine or otherwise select targetcontent based on the target relevance data. For example, targetrelevance component 241 may determine or otherwise select targetedcontent from a set of targeted content, wherein the selected targetedcontent has a highest relevance to a user or group of users. As anexample, target relevance component 241 may generate a relevance scorefor each instance of targeted content in a set of targeted content, andtarget relevance component 241 may select the targeted content with thehighest relevance score, where the highest relevance score indicates themost relevance to the intended user or group of users. In some examples,target relevance component 241 generates relevance scores based onassociations, correlations, or similarities between target relevancedata and the targeted content. Higher relevance scores may be generatedbased on stronger associations, correlations, or similarities betweentarget relevance data and the targeted content.

Other example techniques that may be implemented by target relevancecomponent 241 to select targeted content based on target relevance dataare described in (a) Wan-Shiou Yang, Jia-Ben Dia, Hung-Chi Cheng andHsing-Tzu Lin, “Mining Social Networks for Targeted Advertising,”Proceedings of the 39th Annual Hawaii International Conference on SystemSciences (HICSS′06), Kauia, Hi., USA, 2006, pp. 137a-137a, and (b) C.Xia, S. Guha and S. Muthukrishnan, “Targeting algorithms for onlinesocial advertising markets,” 2016 IEEE/ACM International Conference onAdvances in Social Networks Analysis and Mining (ASONAM), San Francisco,Calif., 2016, pp. 485-492, which are each hereby incorporated byreference in their entirety.

In some examples, target relevance component 241 may select targetedcontent as described in this disclosure and send the targeted content touser applications for display on mobile computing. In some examples, thetargeted content may be displayed in crime element, such as crimeelement 134 in FIG. 1 . For instance, a crime element with targetedcontent may be interspersed between other crime elements, such that auser scrolling or otherwise navigating through a set of crime elementsmay see the crime element that includes the targeted content. In someexamples, in response to receiving an indication of user input thatselects a crime element with targeted content, the user application mayperform additional operations. For instance, the user application maydisplay additional content associated with the targeted content or openanother application that displays additional content associated with thetargeted content. In some examples, the user application may send datato server computing device 200 that indicates the crime element thatincludes the targeted content has been selected by the user. In someexamples, targeted content component 241 may charge a fee to athird-party associated with the targeted content for user selections ofthe targeted content.

FIG. 3 is a block diagram illustrating further details of a mobilecomputing device shown in FIG. 1 , in accordance with one or moreaspects of the present disclosure. Mobile computing device 300 is anexample of mobile computing device 110B, as illustrated and described inFIG. 1 . FIG. 3 illustrates only one particular example of mobilecomputing device 110B, and many other examples of mobile computingdevice 110B may be used in other instances and may include a subset ofthe components included in example mobile computing device 110B or mayinclude additional components not shown in FIG. 3 . In some examples,multiple instances of mobile computing device 110B may interoperatetogether (e.g., smartphone, smartwatch, server, etc.) to provide thefunctionality of mobile computing device 110B described in thisdisclosure.

As shown in the example of FIG. 2 , server computing device 200 includesuser component 326, discussion component 328, location component 330,interface component 332, anonymity component 334, bounty component 336,obfuscator component 338, notification component 340, user data 342,crime data 344, discussion data 346, location data 348, operating system318, one or more storage components 302, one or more input components304, one or more communication components 306, one or more outputcomponents 308, one or more processors 310, and one or morecommunication channels 311.

Communication channels 311 may interconnect one or more devices and/orcomponents of mobile computing device 300 for inter-componentcommunications (physically, communicatively, and/or operatively). Insome examples, communication channels 311 may include a system bus, anetwork connection, an inter-process communication data structure, orany other method for communicating data.

One or more input components 304 of mobile computing device 300 maygenerate or receive data indicating input from one or more humans and/ordevices. Example types of input include tactile, audio, and visualinput, although any suitable types of input may be generated or receivedby input components 304. In one example, input components 304 include apresence-sensitive display, touch-sensitive screen, mouse, keyboard,voice responsive system, video camera, microphone, or any other type ofdevice for detecting input from a human or device.

One or more output components 308 of mobile computing device 300 maygenerate output. Examples of output are tactile, audio, and videooutput. Output components 308 of mobile computing device 300 may includea presence-sensitive display, sound card, video graphics adapter card,speaker, cathode ray tube (CRT) monitor, liquid crystal display (LCD),or any other type of device for generating output to a human or machine.

One or more communication components 306 may allow mobile computingdevice 300 to communicate with external devices and/or systems. In someexamples, communication may be via one or more wired and/or wirelessnetworks, via one or more communication channels that do not include anetwork, and/or a combination of such networks and communicationchannels. Communication components 306 may transmit and/or receivenetwork signals being transmitted and received other devices and/orsystems connected to one or more networks. Examples of communicationcomponents 306 include network interface cards (e.g. such as an Ethernetcard), optical transceivers, radio frequency transceivers, GPSreceivers, or any other type of device that can send and/or receiveinformation. Other examples of communication components 306 may includelong and short wave radios, cellular data radios, wireless networkradios, as well as universal serial bus (USB) controllers, Bluetoothcontrollers and any other suitable components for communication.

One or more storage components 302 of mobile computing device 300 maystore information or instructions that mobile computing device 300processes during operation of mobile computing device 300. For example,storage components 302 may store data that modules or components mayaccess during execution at mobile computing device 300. In someexamples, storage components 302 are temporary memories, meaning that aprimary purpose of storage components 302 is not long-term storage.

Storage components 302 may be configured for short-term storage ofinformation as volatile memory and therefore not retain stored contentsif powered off. Examples of volatile memories include random accessmemories (RAM), dynamic random access memories (DRAM), static randomaccess memories (SRAM), and other forms of volatile memories known inthe art.

Storage components 302 may be configured to store larger amounts ofinformation than volatile memory and may further be configured forlong-term storage of information as non-volatile memory space and retaininformation after power on/off cycles. Examples of non-volatile memoriesinclude magnetic hard discs, optical discs, floppy discs, flashmemories, or forms of electrically programmable memories (EPROM) orelectrically erasable and programmable (EEPROM) memories.

Storage components 302, in some examples, include one or morecomputer-readable storage media. In some examples, storage components302 represent non-transitory computer readable storage medium that storeinstructions later executed by one or more processors 310 duringoperation of mobile computing device 300. For example, storagecomponents 302 may store program instructions and/or information (e.g.,data) associated with components included application layer 316 ofmobile computing device 300. Application layer 316 may include one ormore applications such as user application 317, which may be an exampleof user application 128B in FIG. 1 . User application 317 may includelogic tier 322 with one or more components that perform one or moreoperations and data tier 324 with one or more datastores or otherconfigurations of data.

One or more processors 310 may implement functionality and/or executeinstructions within mobile computing device. For example, processors 310on mobile computing device 300 may receive and execute instructionsstored by storage components 302 that execute the functionality ofcomponents included in application layer 316. The instructions executedby processors 310 may cause mobile computing device 300 toread/write/etc. data that is stored within storage components 302.Processors 310 may execute instructions of components included inapplication layer 316 to cause mobile computing device 300 to performthe operations described in this disclosure. That is, components inapplication layer 316 may be operable by processors 310 to performvarious operations, actions, and/or functions of mobile computing device300 in accordance with one or more aspects of the present disclosure.

As shown in FIG. 3 , mobile computing device 300 includes user component326. User component 326 may send one or more types of information viaanonymization network 120 from a user application (e.g., userapplication 128B), which server application 217 may use to generate aunique user identifier for user 108B, which is stored in user data 242and used by server application 217 in accordance with techniques of thisdisclosure. The various types of information are described in FIG. 2 .User component 326 may receive a unique user identifier for user 108Bfrom server application 217 at the time of user identifier creation, andstore the user identifier as user data 342. In some examples, usercomponent 326 may encrypt user data 342. In some examples, anauthentication credential may be associated with the user identifier andstored in user data 342. In some examples, server application 217 mayonly process requests that include a valid combination of useridentifier and authentication credential.

User application 317 may include discussion component 328. Discussioncomponent 328 may generate one or more user interfaces in which user108B may submit discussion information and/or view discussioninformation. Discussion information and any metadata for discussioninformation may be stored as discussion data 346. In some examples,discussion component 328 may generate and/or display discussion data 346that corresponds to discussion information such as metadata about thediscussion information, including but not limited to discussion messagescores, proximity elements and any other data relating to discussioninformation or a discussion message.

User application 317 may include location component 330. Locationcomponent 330 may generate location data 348 according to one or moretechniques described in FIG. 1 . In some examples, location component330 sends location data 348 to server application 217 for processing inaccordance with one or more techniques of this disclosure. In someexamples, location component 330 may receive location data fromoperation system 318 and/or a runtime environment executing at mobilecomputing device 300.

User application 317 may include interface component 332. Interfacecomponent 332 may include one or more libraries and/or runtimecomponents that user application 317 may use to send and receive datawith other computing devices such as server application 217.

User application 317 may include anonymity component 334. Anonymitycomponent 334 may implement one or more specifications or functions thatanonymize data sent from user application 317 and/or mobile computingdevice 300 to server computing device 200. For instance, anonymitycomponent 334 may implement or other operate in accordance with the TorProtocol Specification as described in FIG. 1 . Network communicationsinitiated by user application 317 to server application 217 may beanonymized by anonymity component 334, which may communicate with one ormore relays in an anonymization network. In other examples, anonymitycomponent 334 may implement any other techniques that may anonymize thesource device from the destination device, as described in FIG. 1 .

User application 317 may include bounty component 336. Bounty component336 may generate one or more user interfaces in which user 108B maysubmit payments for bounties and/or receive remittances associated withbounties. For example, bounty component 336 may enable a user to provideinput that specifies a bounty amount for a particular crime, accountinformation, and any other information described in FIG. 1 . Bountycomponent 336 may send such data to server application 217, which mayassociate the bounty payment with a particular bounty for a crime.Bounty component 336 may enable a user to provide input that enables theuser to receive a bounty payment as a remittance when released by serverapplication 217. In some examples, bounty component 336 may enable theuser to receive payment through any number of different paymentprocessors (e.g., PayPal, Western Union, Batchex, GiftBit, BitCoin,Ethereum, Square, Google Wallet, Apple Pay, etc.).

User application 317 may include obfuscator component 338. Obfuscatorcomponent 338 may reduce or prevent doxing of individuals in textprovided to user application 317, such as in a discussion message, crimedata, or any other information. In some examples, doxing may meanbroadcasting private or identifiable information (especially personallyidentifiable information) about an individual or organization in apublicly viewable way. Obfuscator component 338 may implement one ormore techniques to reduce or prevent doxing of individuals.

As described herein, obfuscator component 338 may determine whether, forexample, text in a discussion message, includes private or identifiableinformation about an individual or organization that may dox theindividual. As an example, obfuscator component 338 may perform a lookupof text submitted by a user against a set of words that represent personnames, although any set of words may be used. In some examples,obfuscator component 338 may determine a likelihood or score that text(e.g., a word or set of words) includes private or identifiableinformation about an individual or organization that may dox theindividual, and if the likelihood or score satisfies a threshold (e.g.,greater than or equal to), then obfuscator component 338 may determinethat the text includes private or identifiable information about anindividual or organization that may dox the individual.

In some examples, if obfuscator component 338 determines that the textincludes private or identifiable information about an individual ororganization that may dox the individual, obfuscator component 338 mayassociate a label with the word (e.g., name), such that when displayedat a mobile computing device, the text with the label is obfuscatedusing one or more techniques. Such techniques may include obfuscatingeach vowel, every n-th character of the word, or the entire word to nameonly a few examples.

In some examples, a label may not be associated with the word (e.g.,stored as metadata with the word), but the word or set of words may beobfuscated by obfuscator component 338 and stored as an obfuscated wordin, e.g., discussion data 346. In some examples, certain user types orroles may be able to view non-obfuscated words that are obfuscated for adifferent types or roles. For examples, a special user (e.g., source ofauthority or law enforcement) may be assigned a user type or role inuser data 342 with the user identifier that permits the source ofauthority user to view non-obfuscated words that are obfuscated for adifferent types or roles, while a non-special user may not view theobfuscated words. A user application executing at a mobile device asdescribed in this disclosure may receive, from server application 217,obfuscated words based on different types or roles, or the userapplication may determine based on a label associated with a words thatuser application will obfuscate the word before it is displayed in theuser interface. In some examples, server application 217 may encrypt orotherwise encode obfuscated words or text (e.g., with a key in someexamples), such that only certain user types or roles may causeobfuscator component 338 to decrypt or decode the obfuscated words ortext to view the non-obfuscated words or text. In any case, obfuscatorcomponent 338 may implement one or more techniques to prevent or limitviewing of private or identifiable information about an individual ororganization that may dox the individual, which may have been submittedby one or more users.

User application may include notification component 340. In someexamples, notification component 340 may receive data from serverapplication 217, which notification component 340 causes operationsystem 318 and/or one or more runtime components to generate anotification with information. Notifications may include audio, haptic,and/or visual output at the mobile computing device. Examplenotifications may include but are not limited to: a user receives aprivate message, a user receives a bounty payment as a remittance, abounty payment is returned to the user, a discussion message generatedby the user is replied to be another user, activity occurs on a crime orbounty marked as a favorite by the user, a new crime occurs and the useris within a threshold distance of the crime and within a threshold timeof when the crime occurred, or any other event occurs for which anotification is generated.

FIG. 4 is a conceptual diagram of a prediction component 402 inaccordance with techniques of this disclosure. Prediction component 402may be an example of prediction component 234 as shown in FIG. 2 . Insome examples, prediction component 402 may receive a crime profile 404.A crime profile may include any data that is descriptive of a crime orthat relates to a crime. Prediction component 402 may generate a bountyprofile 412, which may indicate a bounty amount, bounty time, and/orother characteristics of a bounty, where bounty profile 412 may includea likelihood value that may satisfy a likelihood threshold, and thelikelihood threshold indicates that the bounty profile, if applied tothe crime, may produce information from one or more users that solvesthe particular crime, discourages future crime, and/or improves thesafety of the neighborhood or region around the crime. In this way,prediction component 402 may output for display, for a particular crime,one or more bounty amounts that may produce information from one or moreusers that solves the particular crime, discourages future crime, and/orimproves the safety of the neighborhood or region around the crime.

As shown in FIG. 4 , prediction component 402 may include extractioncomponent 406, model 410, and learning component 408. Extractioncomponent 406 may extract features from a crime profile 404, whichextraction component 406 may configure into a feature vector. In someexamples, model 410 (e.g., a bounty model) may be trained by learningcomponent 408 using supervised and/or reinforcement learning techniques.Model 410 may be implemented using any number of models for supervisedand/or reinforcement learning, such as but not limited to a decisiontree, artificial neural networks, support vector machine, naïve Bayesnetwork, or k-nearest neighbor model.

In some examples, learning component 408 may train model 410 based on atraining set. The training set may include a set of data structured asfeature vectors (or other suitable form), where each feature in thefeature vector represents a characteristic of a bounty, crime to whichthe bounty is associated, or any other information associated with abounty. The feature vector may, for example, include a first featurethat indicates a bounty amount and a second feature whether the bountywas released as a remittance. Features in the feature vector and/or in acrime profile may include but are not limited to: crime type, crimelocation, crime time, discussion velocity, total discussion messages,text from discussion information, number of users at each distancethreshold replying and/or submitting discussion information, paymenttype, discussion message scores (total score increases, total scoredecreases, net score, velocity of score increases and/or decreases, orany other result from one or more functions applied to discussionmessage scores), amount of obfuscated words, whether the bounty issponsored by a source of authority, or any other information describedin this disclosure or that otherwise may be used to predict whether abounty amount will produce information from one or more users thatsolves the particular crime, discourages future crime, and/or improvesthe safety of the neighborhood or region around the crime. Training datamay be selected from learning data 422, which includes crime data 414,bounty data 416, discussion data 418, and/or location data 420, whichmay be examples of like-named data in FIG. 2 . Other data may also beused such as user data.

By training model 410 based on training data, model 410 may beconfigured by learning component 408 to generate a set of one or morebounty amounts that, for a particular crime profile, are likely toresult in the release of a bounty as a remittance in response toinformation produced from one or more users that solves the particularcrime, discourages future crime, and/or improves the safety of theneighborhood or region around the crime. In some examples, each bountyamount from the set of bounty amounts may be associated with acorresponding likelihood value, such as a probability or a score. Insome examples, bounty profile 412 includes the set of one or more bountyamounts and/or respective likelihood values for the bounty amounts. Insome examples, a crime profile 404 may be submitted to predictioncomponent 402, and trained model 410 may output a bounty profile 412,which can be output for display. In some examples, bounty profile 412 isoutput for display in a graphical user interface to indicate the amountof a bounty that, for a particular crime profile, are likely to resultin the release of a bounty as a remittance in response to informationproduced from one or more users that solves the particular crime,discourages future crime, and/or improves the safety of the neighborhoodor region around the crime. In some examples prediction component 402may select the highest likelihood value or a set of likelihood valuesthat satisfy a threshold (e.g., greater than or equal to). In someexamples, the output of model 410, such as bounty profile 412 may beused by learning component 408 to train model 410 while predictionoperation 402 is in operation with one or users.

In some examples, predication component 402 may receive a crime profile404 comprising data that characterizes the crime. Prediction component402 may apply the data of the crime profile that characterizes the crimeto a bounty model 410 that predicts a likelihood that a remittanceamount will produce information about the crime from one or more users.Prediction component 402 may perform at least one operation based atleast in part on the likelihood that the remittance amount will produceinformation about the crime from one or more users. In some examples,prediction component 402 may select a set of training instances, eachtraining instance comprising an association between a remittance amountand data that characterizes a crime. In some examples, predictioncomponent 402 may, for each respective training instance, and based on arespective remittance amount and respective data that characterizes acrime for the training instance, modify the bounty model 410 to change alikelihood predicted by the bounty model 410 for a remittance amount inresponse to a subsequent crime profile applied to the bounty model 410.

FIG. 5 is a flow diagram illustrating example operations of a servercomputing device, in accordance with techniques of this disclosure. Forpurposes of illustration only, the example operations (500) may beperformed by server computing device 116A in FIG. 1 or server computingdevice 200 in FIG. 2 . Using server computing device 116A as an example,server computing device 116A may be communicatively coupled to aplurality of mobile computing devices. Server computing device 116A mayreceive, using an anonymization network and from a respective mobilecomputing device of the plurality of mobile computing devices, arespective set of locations of the respective mobile computing (502).The respective source addresses of the plurality of mobile computingdevices may be unknown to server 116A computing device based on usingthe anonymization network.

Server computing device 116A may generate, based at least in part on adetermination that a location from the respective set of locations ofthe respective mobile computing device is within a threshold distance ofa location of a crime, a proximity indication that a user associatedwith the respective mobile computing device is proximate to the crime(504). Server computing device 116A may, in response to receiving anindication of a remittance for the crime, generate an associationbetween the remittance and the crime (506). Server computing device 116Amay receive, using the anonymization network, descriptive data generatedby the user that is descriptive of the crime (508). Server computingdevice 116A may send the descriptive data to at least one other mobilecomputing device of the plurality of mobile computing devices that isassociated with at least one other user (510).

Server computing device 116A may receive, from the at least one othermobile computing device that outputs a user interface in which thedescriptive data is associated with the proximity indication, anindication to release the remittance provided by the at least one otheruser (512). In response to receiving the indication, server computingdevice 116A may perform at least one operation that provides theremittance to the user (514).

FIG. 6 is a flow diagram illustrating example operations of a mobilecomputing device, in accordance with techniques of this disclosure. Forpurposes of illustration only, the example operations 600 may beperformed by mobile computing device 110B in FIG. 1 or mobile computingdevice 300 in FIG. 3 . Using mobile computing device 110B as an example,mobile computing device 110B may send, using an anonymization networkand to a remote computing device, a respective set of locations of themobile computing device (602). I some examples, the respective sourceaddress of mobile computing device 110B is unknown to the remotecomputing device. The respective set of locations may be usable by theremote computing device to generate, based at least in part on alocation from a set of locations being within a threshold distance of alocation of a crime, a proximity indication that a user associated withmobile computing devices is proximate to the crime.

Mobile computing device 110B may receive an indication of a remittancefor the crime from the remote computing device (604). In some responseto receiving the indication, mobile computing device 110B maycontemporaneously output for display an indication of the remittance inassociation with an indication of the crime (606). Mobile computingdevice 110B may receive descriptive data generated by the user that isdescriptive of the crime (608). Mobile computing device 110B may send,using the anonymization network, the descriptive data to the remotecomputing device (610). Mobile computing device 110B may output a userinterface in which the descriptive data is associated with the proximityindication (612). Mobile computing device 110B may receive, from theremote computing device, a message that the remittance is provided tothe user (614). In response to receiving the message, mobile computingdevice 110B may output for display an indication that the remittance isprovided to the user (616).

FIG. 7 illustrates a crime map graphical user interface 700 that may beoutput by a mobile computing device in accordance with techniques ofthis disclosure. Graphical user interface (GUI) 700 may be output fordisplay by mobile computing device 110B of FIG. 1 or mobile computingdevice 300 of FIG. 3 . Although graphical elements having variousfunctionality are output for display at certain locations of graphicaluser interface 700, such graphical elements may, in different examples,be positioned in different locations of graphical user interfaceswithout deviating from the spirit and scope of the techniques of thisdisclosure. Although graphical elements having various functionality areoutput for display with certain appearances, shapes, size, animations,or any other visual characteristics in graphical user interface 700,such graphical elements may, in different examples, be output fordisplay with different appearances, shapes, size, animations, or anyother visual characteristics of graphical user interfaces withoutdeviating from the spirit and scope of the techniques of thisdisclosure.

GUI 700 includes map graphical element 702. Map graphical element 702may illustrate a map of a particular area, such as a city. In someexamples, map graphical element 702 may be scrollable, in response touser input, in any direction on an X-Y plane, such that different areasof an area may be output for display. May graphical element 702 may beimplemented as a control provided in a library, runtime, or othercomponent.

As shown in FIG. 7 , map graphical element 702 may include one or morecrime location indicators, such as indicator 704. Each crime locationindicator 704 may represent a location of a crime that has occurred at aparticular location within a map of a particular area. Crime locationindicator 704 may be based on data sent by a server computing device tomobile computing device 110B. The data sent by the server computingdevice may include a set of crime locations for different crimes and mayinclude other data about the crimes including but not limited to, timeof crime, type of crime, street address of crime or any other suitabledata or data described in this disclosure. Mobile computing device 110Bmay populate map graphical element 702 with crime location indicatorsbased on the data received from the server computing device. In someexamples, the visual appearance of a crime location indicate mayrepresent a type of crime. For example, crime location indicator 704 mayindicate a Theft crime based the appearance of an outstretched handicon.

In some examples, GUI 700 may include crime element 706. Initially, whenmap graphical element 702 is output for display, crime element 706 maynot be shown. In response to receiving an indication of user input toselect a crime location indicator in map graphical element 702, mobilecomputing device 110B may output for display crime element 706. In someexamples, the indication of user input may re-center map graphicalelement 702, such that the selected crime location indicator is at thecenter of map graphical element 702. In any case, crime element 706 mayinclude crime information for the crime that corresponds to the selectedcrime location indicator. Crime element 706 may include crimeinformation as described with respect to crime element 134 of FIG. 1 .In other examples, crime element 706 may include additional or lessinformation than crime element 134 of FIG. 1 . In some examples, anindication of user input that selects crime element 706 may causecomputing device 110B to output for display graphical user interface900, as shown in FIG. 9 .

GUI 700 may include crime user interface indicator 708, private messageuser interface indicator 710, and me user interface indicator 712. Crimeuser interface indicator 708, when selected by an indication of userinput, may cause mobile computing device 110B to output GUI 700. Privatemessage user interface indicator 710, when selected by an indication ofuser input, may cause mobile computing device 110B to output GUI 1100 inFIG. 11 . Me user interface indicator 712, when selected by anindication of user input, may cause mobile computing device 110B tooutput GUI 1400 in FIG. 14 .

GUI 700 may include search indicator 714 that, when selected by anindication of user input, outputs for display an input field. A user mayenter text into the input field. Mobile computing device 110B may searchwithin the user application for content that corresponds to the enteredtext. The content may be output for display within a graphical userinterface. GUI 700 may include list indicator 716 that, when selected byan indication of user input, may cause mobile computing device 110B tooutput GUI 800 in FIG. 8 .

FIG. 8 illustrates a crime list summary graphical user interface 800that may be output by a mobile computing device in accordance withtechniques of this disclosure. Graphical user interface (GUI) 800 may beoutput for display by mobile computing device 110B of FIG. 1 or mobilecomputing device 300 of FIG. 3 . Although graphical elements havingvarious functionality are output for display at certain locations ofgraphical user interface 800, such graphical elements may, in differentexamples, be positioned in different locations of graphical userinterfaces without deviating from the spirit and scope of the techniquesof this disclosure. Although graphical elements having variousfunctionality are output for display with certain appearances, shapes,size, animations, or any other visual characteristics in graphical userinterface 800, such graphical elements may, in different examples, beoutput for display with different appearances, shapes, size, animations,or any other visual characteristics of graphical user interfaces withoutdeviating from the spirit and scope of the techniques of thisdisclosure.

As shown in FIG. 8 , GUI 800 may include a set of crime elements802A-802D (“crime elements 802”). Although four crime elements areillustrated in FIG. 8 , any number of crime elements may be shown. GUI800 may be scrollable, such that in response to receiving an indicationof user input, crime elements 802 may scroll up or down along thelonger-side, vertical axis of GUI 800. In some examples, crimeinformation of each respective crime element corresponds to a crimeassociated with a crime location indicator as shown in FIG. 7 . Forinstance, if mobile computing device 110B receives an indication of userto select list indicator 716 in FIG. 7 , then mobile computing device110B may output for display GUI 800 with a list of crime elements thatcorrespond to crimes of the crime location indicators that were visibleor within a threshold distance of a point (e.g., center of map graphicalelement) in GUI 700. In some examples, selecting a crime element, suchas crime element 802A may cause mobile computing device 110B to outputfor display a crime discussion graphical user interface, such as crimediscussion user interface 900 as shown in FIG. 9 .

FIG. 9 illustrates a crime discussion graphical user interface 900 thatmay be output by a mobile computing device in accordance with techniquesof this disclosure. Graphical user interface (GUI) 900 may be output fordisplay by mobile computing device 110B of FIG. 1 or mobile computingdevice 300 of FIG. 3 . Although graphical elements having variousfunctionality are output for display at certain locations of graphicaluser interface 900, such graphical elements may, in different examples,be positioned in different locations of graphical user interfaceswithout deviating from the spirit and scope of the techniques of thisdisclosure. Although graphical elements having various functionality areoutput for display with certain appearances, shapes, size, animations,or any other visual characteristics in graphical user interface 900,such graphical elements may, in different examples, be output fordisplay with different appearances, shapes, size, animations, or anyother visual characteristics of graphical user interfaces withoutdeviating from the spirit and scope of the techniques of thisdisclosure.

GUI 900 may include crime element 902. Crime element 902 may includecrime information as described with respect to crime element 134 of FIG.1 . In other examples, crime element 902 may include additional or lessinformation than crime element 134 of FIG. 1 . GUI 900 may include inputfield 904. Input field 904 may receive input from a user (e.g., text,images, videos, audio, location, or any other content), which may bestored (e.g., at a server computing device) in association with crimeinformation for crime element 902. In some examples, in response to auser providing input, a new discussion element (e.g., as described inFIG. 1 ), such as discussion element 906A may be output for display inGUI 900 with the discussion information corresponding to the providedinput. In some examples, the server computing device that receives suchdiscussion information may send such discussion information to othermobile computing devices, which can also respectively output for displaya discussion element with the discussion information. In some examples,a discussion element may be output for display (e.g., in a notificationand/or GUI such as GUI 900) in real-time in response to receiving thediscussion information. Discussion elements 906 may include replies fromdifferent users with discussion information that corresponds to thecrime indicated in crime element 902. Discussion elements 906A and 906Bmay include discussion information as described with respect todiscussion element 136A of FIG. 1 . In other examples, crime element 902may include additional or less information than discussion element 136Aof FIG. 1 .

FIG. 10 illustrates a submit bounty graphical user interface 1000 thatmay be output by a mobile computing device in accordance with techniquesof this disclosure. Graphical user interface (GUI) 1000 may be outputfor display by mobile computing device 110B of FIG. 1 or mobilecomputing device 300 of FIG. 3 . Although graphical elements havingvarious functionality are output for display at certain locations ofgraphical user interface 1000, such graphical elements may, in differentexamples, be positioned in different locations of graphical userinterfaces without deviating from the spirit and scope of the techniquesof this disclosure. Although graphical elements having variousfunctionality are output for display with certain appearances, shapes,size, animations, or any other visual characteristics in graphical userinterface 1000, such graphical elements may, in different examples, beoutput for display with different appearances, shapes, size, animations,or any other visual characteristics of graphical user interfaces withoutdeviating from the spirit and scope of the techniques of thisdisclosure.

GUI 1000 may include one or more text and/or input fields that includeinformation describing a crime to which a bounty will be assigned. Forinstance, GUI 1000 may be output for display in response to a userproviding an indication of user input to select a bounty submit icon,such as bounty submit icon 149 as illustrated in FIG. 1 , although anysuitable user input and/or icon/indicator may be used to cause GUI 1000to be displayed. In any event, GUI 1000 may include crime typeinformation 1002, which may include a crime type (e.g., “Theft”) and adescriptive label to indicate the type of information (e.g., “CrimeType”). GUI 1000 may include crime street address information 1004,which may include a street address of a crime (e.g., “001XX W KinzieSt”) and a descriptive label to indicate the type of information (e.g.,“Crime Street Address”). GUI 1000 may include crime city/state/zipinformation 1006, which may include a city, state, and/or zip code of acrime (e.g., “Chicago, Ill., 60654”) and a descriptive label to indicatea type of information (e.g., “Crime City, State, Zip”). GUI 1000 mayinclude crime date information 1008, which may include a date of a crime(e.g., “03-10-2017”) and a descriptive label to indicate a type ofinformation (e.g., “Crime Date”). GUI 1000 may include crime timeinformation 1010, which may include a time of a crime (e.g., “9:35 PM”)and a descriptive label to indicate a type of information (e.g., “CrimeTime”).

GUI 1000 may include bounty information 1012, which may include anamount of a bounty that a user will assign to a crime and a descriptivelabel to indicate a type of information (e.g., “Bounty Amount”). Asdescribed in this disclosure a bounty amount may be any quantity ofcurrent or other denomination of value. GUI 1000 may include a selectpayment type indicator 1014. Payment select indicator 1014 may be abutton as shown in FIG. 10 or may be any other suitable graphicalelement. In any case, when selected by an indication of user input,payment select indicator 1014 may present a graphical user interface fora user to select a payment type (e.g., PayPal, Bitcoin, or any othersuitable payment type). In some examples, select payment indicator 1014may initiate the transaction to assign the bounty amount with the crimewithout presenting a GUI for a user to select a payment type. Forinstance, a default payment type may already be configured and used forthe transaction without requiring a selection of a payment type.

FIG. 11 illustrates a private message summary graphical user interface1100 that may be output by a mobile computing device in accordance withtechniques of this disclosure. Graphical user interface (GUI) 1100 maybe output for display by mobile computing device 110B of FIG. 1 ormobile computing device 300 of FIG. 3 . Although graphical elementshaving various functionality are output for display at certain locationsof graphical user interface 1100, such graphical elements may, indifferent examples, be positioned in different locations of graphicaluser interfaces without deviating from the spirit and scope of thetechniques of this disclosure. Although graphical elements havingvarious functionality are output for display with certain appearances,shapes, size, animations, or any other visual characteristics ingraphical user interface 1100, such graphical elements may, in differentexamples, be output for display with different appearances, shapes,size, animations, or any other visual characteristics of graphical userinterfaces without deviating from the spirit and scope of the techniquesof this disclosure.

GUI 1100 may include a set of private message summary elements1102A-1102B (“private message summary elements 1102”). Although twoprivate message summary elements 1102 are shown in GUI 1100, any numberof private message summary elements may be shown in GUI 1100. A privatemessage summary element (e.g., 1102A), may include a summary of privatediscussion information that is exchanged in a message conversationbetween a user and a source of authority (e.g., a law enforcementagency), such as shown in FIG. 12 . Private message summary element1102A may include private message icon 1104, which may visuallyrepresent a message conversation between a user and a source ofauthority. In some examples, private message summary element 1102A mayinclude user identification element 1106, which is a user identifier fora user that provided private information 1110. All or a portion ofprivate information 1110 may be included in private message summaryelement 1102A. Private message summary element 1108 may includetime-elapsed value 1108, which indicates the amount of time elapsedbetween a current time that private message summary element 1108 isdisplay and when a user submitted private information 1110. In someexamples, private message summary element 1102A may include crimeinformation 1112, which may include crime type, crime street address,crime city, crime state, crime zip code, crime time, crime date, and/orany other characteristics or descriptive data of a crime. In someexamples, the private information 1110 corresponds to the most recentprivate information exchanged in a message conversation between a userand a source of authority.

FIG. 12 illustrates a private message graphical user interface 1200 thatmay be output by a mobile computing device in accordance with techniquesof this disclosure. Graphical user interface (GUI) 1200 may be outputfor display by mobile computing device 110B of FIG. 1 or mobilecomputing device 300 of FIG. 3 . Although graphical elements havingvarious functionality are output for display at certain locations ofgraphical user interface 1200, such graphical elements may, in differentexamples, be positioned in different locations of graphical userinterfaces without deviating from the spirit and scope of the techniquesof this disclosure. Although graphical elements having variousfunctionality are output for display with certain appearances, shapes,size, animations, or any other visual characteristics in graphical userinterface 1200, such graphical elements may, in different examples, beoutput for display with different appearances, shapes, size, animations,or any other visual characteristics of graphical user interfaces withoutdeviating from the spirit and scope of the techniques of thisdisclosure.

GUI 1200 may include private message summary element 1202 and one ormore private message elements 1204A-1204C (“private message elements1204”). Private message elements 1204 may respectively representmessages or other content shared between a user and a source ofauthority. In some examples, private message elements may only beviewable to a particular user that is operating the mobile computingdevice and one or more other users that are assigned a particular typeof role (e.g., are a source of authority). In this way, a user mayprivately communicate with a source of authority in order to shareadditional or different information that may not be shared in GUI 900.

Private message element 1204A, for example, may include user icon 1216,which may represent a particular user or a particular role or type ofuser that provided private message information 1206. Private messageinformation 1206 may be any type of content such as text, images,videos, audio, or any other type of content. Private message information1206 may be created and submitted by a user. Private message element1204A may include user identification element 1208, which may be aunique identifier of the user that submitted private message information1206. Private message element 1204A may include reply element 1210,which when selected by a user, changes GUI 1200 (e.g., outputs an inputfield or other graphical element) to enable a user to provide content inreply to private message information 1206. Private message element 1204Amay include timestamp 1212, which may indicate a date and/or time whenthe private message information 1206 was created. In some examples,private message element 1204A may include time-elapsed value 1214, whichindicates an amount of time elapsed between the date and time whenmessage information 1206 was created and the current time whentime-elapsed value 1214 is displayed.

FIG. 13 illustrates a release payment graphical user interface 1300 thatmay be output by a mobile computing device in accordance with techniquesof this disclosure. Graphical user interface (GUI) 1300 may be outputfor display by mobile computing device 110B of FIG. 1 or mobilecomputing device 300 of FIG. 3 . Although graphical elements havingvarious functionality are output for display at certain locations ofgraphical user interface 1300, such graphical elements may, in differentexamples, be positioned in different locations of graphical userinterfaces without deviating from the spirit and scope of the techniquesof this disclosure. Although graphical elements having variousfunctionality are output for display with certain appearances, shapes,size, animations, or any other visual characteristics in graphical userinterface 1300, such graphical elements may, in different examples, beoutput for display with different appearances, shapes, size, animations,or any other visual characteristics of graphical user interfaces withoutdeviating from the spirit and scope of the techniques of thisdisclosure.

GUI 1300 may be output for display so that a user may release aremittance for a bounty to one or more users. For instance, a source ofauthority may identify information that is particularly useful orvaluable to solve the particular crime, discourage future crimes, and/orimprove the safety of the neighborhood or region around the crime.Accordingly, the user may provide an indication of user input to selectan icon or otherwise cause mobile computing device 110B to output GUI1300 for display. GUI 1300 may include crime element 1304, which mayhave the same or similar functionality to crime elements described inthis disclosure. In some examples, GUI 1300 may initially indicate aremaining bounty amount that represents the total bounty amount for acrime. In some examples, GUI 1300 may include discussion elements, suchas discussion element 1306, which may include the same or similarfunctionality as other discussion elements described in this disclosure.In some examples, a payment selector, such as payment selector 1308, maybe associated with each respective discussion element. Payment selector1308 may be a graphical element that a user may select or adjust toassign some portion of remaining bounty amount 1310 to the user thatprovided discussion information in the discussion element to which thepayment selector 1308 is associated. For instance, a user may changepayment selector 1308 such that $11,000 of the total bounty amount isassigned to the user that provided the discussion information fordiscussion element 1306. Similarly, the remaining bounty amount may beassigned to one or more other users.

GUI 1300 may include bounty payment element 1302. Bounty payment element1302 may be any selectable graphical element such as a button. Whenbounty payment element 1302 is selected, remittances may be provided toeach respective user as described in this disclosure based on therespective values of the payment selectors, such as payment selector1308. In this way, users may be compensated (in some cases anonymously)in exchange for providing information that is useful or valuable tosolve the particular crime, discourage future crimes, and/or improve thesafety of the neighborhood or region around the crime.

FIG. 14 illustrates a user graphical user interface 1400 that may beoutput by a mobile computing device in accordance with techniques ofthis disclosure. Graphical user interface (GUI) 1400 may be output fordisplay by mobile computing device 110B of FIG. 1 or mobile computingdevice 300 of FIG. 3 . Although graphical elements having variousfunctionality are output for display at certain locations of graphicaluser interface 1400, such graphical elements may, in different examples,be positioned in different locations of graphical user interfaceswithout deviating from the spirit and scope of the techniques of thisdisclosure. Although graphical elements having various functionality areoutput for display with certain appearances, shapes, size, animations,or any other visual characteristics in graphical user interface 1400,such graphical elements may, in different examples, be output fordisplay with different appearances, shapes, size, animations, or anyother visual characteristics of graphical user interfaces withoutdeviating from the spirit and scope of the techniques of thisdisclosure.

GUI 1400 may include bounty or remittance received region 1402 and abounty or remittance paid region 1404. Regions 1402 and 1404 may eachinclude a list of remittance elements, such as remittance element 1406and remittance element 1408. Remittance element 1406, may include orrepresent details of a remittance received by the user, while remittanceelement 1408 may include or represent details of a remittance paid bythe user. In some examples, remittance element 1406 and/or 1408 may beselectable. For instance, if a user provides user input to selectremittance element 1406, mobile computing device 110B may generate fordisplay a different graphical user interface which, for example, mayenable the user to select a type of payment (e.g., PayPal, BitCoin,etc.) that the user may receive the remittance.

Remittance element 1406 may include a crime type icon 1414, whichindicates the type of crime for which the bounty was received.Remittance element 1406 may include crime details 1410, which as streetaddress, city, state, zip code, date and time of the crime for which theremittance is paid. In some examples, remittance element 1406 mayinclude the remittance amount 1416. In some examples, remittance element1406 may include a remittance status, which may include Pending,Received, or any other status. Similarly, remittance element 1408 for aremittance that is paid may include a remittance status such as Posted,Paid, or any other status.

Although systems and techniques herein have been described with respectto crimes, these systems and techniques may be adapted within the spiritand scope of this disclosure to any event, occurrence, gathering,assembly, environment or other instance where users may shareinformation anonymously and/or can be compensated for such information.

Example 1: A system comprising: a plurality of mobile computing devicesassociated with a plurality of respective users; an anonymizationnetwork; at least one server computing device communicatively coupled toeach mobile computing device of the plurality of mobile computingdevices, and wherein each respective mobile computing device of theplurality of mobile computing devices sends, using the anonymizationnetwork, a respective set of locations of the respective mobilecomputing to the at least one server computing device, such that theplurality of mobile computing devices are anonymous to the at least oneserver computing device; wherein the at least one server computingdevice, based at least in part on a determination that a location from aset of locations of one of the mobile computing devices is within athreshold distance of a location of a crime, generates a proximityindication that a user associated with the one of the mobile computingdevices is proximate to the crime; wherein the at least one servercomputing device, in response to receiving an indication of a remittancefor the crime from at least one other user, stores an associationbetween the remittance and the crime; wherein the at least one servercomputing device, in response to receiving, using the anonymizationnetwork, descriptive data generated by the user that is descriptive ofthe crime, sends the descriptive data to at least one other mobilecomputing device of the plurality of computing devices that isassociated with the at least one other user; and wherein the servercomputing device performs at least one operation that provides theremittance to the user in response to receiving, from the at least oneother mobile computing device that outputs a user interface in which thedescriptive data is associated with the proximity indication, anindication to release the remittance provided by the at least one otheruser.

Example 2: The system of Example 1, wherein the one of the mobilecomputing devices is a first mobile computing device and the at leastone other mobile computing device is a second mobile computing device;wherein the anonymization network comprises a plurality of relay networkdevices, wherein the plurality of relay network devices includes aningress relay network device communicatively coupled to the first mobilecomputing device, and the plurality of relay network devices comprisesan egress relay network device communicatively coupled to the at leastone server computing device, and wherein a set of intermediate relaynetwork devices in a communication route between the ingress and egressrelay network devices provide the communicate route between the firstmobile computing device and the at least one server computing device;wherein the descriptive data is received by the ingress relay networkdevice from the first mobile computing device, and wherein each relaynetwork device in the set of relay network devices encrypts thedescriptive data before the descriptive data is forwarded to anotherrelay network device in the communicate route; and wherein the egressrelay network device decrypts the descriptive data and forwards thedescriptive data to the at least one server computing device, such thatthe plurality of mobile computing devices are anonymous to the at leastone server computing device.

Example 3: The system of any of Examples 1-2, wherein respectiveidentifiers of the plurality of mobile computing devices are respectivesource network addresses of the respective mobile computing devices, andwherein the respective identifiers of the plurality of mobile computingdevices are unknown to the at least one server computing device.

Example 4: The system of any of Examples 1-4, wherein the one of themobile computing devices is a first mobile computing device; wherein adetermination by the at least one server computing device that thelocation of the first mobile computing device is within a thresholddistance of the location of the crime is based at least in part on adetermination by the server computing device that a time durationbetween a first timestamp of the location of the first mobile computingdevice and a second timestamp of the crime satisfies a threshold.

Example 5: The system of any of Examples 1-5, wherein the proximityindication indicates at least one of a degree or an amount of at leastone of a physical distance or temporal distance between the user and thecrime.

Example 6: The system of any of Examples 1-5, wherein the at least oneother mobile computing device outputs the user interface tocontemporaneously include the descriptive data in association with theproximity indication and an amount of the remittance.

Example 7: The system of any of Examples 1-6, wherein the servercomputing device, to perform at least one operation that provides theremittance to the user: selects an account identifier of the user;generates a message that comprises the account identifier of the user,an account identifier of an account controlled by an operator of aservice provided by the at least one server computing device, and anamount of the remittance; and sends the message to at least one remotecomputing device that executes a transaction that transfers at least aportion of the amount of the remittance from the account controlled bythe operator to an account associated with the account identifier of theuser.

Example 8: The system of any of Examples 1-7, wherein the portion of theamount of the remittance is denominated in a cryptocurrency and theaccount associated with the account identifier of the user isdenominated in the cryptocurrency.

Example 9: The system of any of Examples 1-8, wherein the portion of theamount is a first portion, wherein the at least one server computingdevice, to perform at least one operation that provides the remittanceto the user, determines a second portion of the amount based at least inpart on the amount of the remittance and generates the first portion ofthe amount of the remittance based at least in part on the secondportion.

Example 10: The system of any of Examples 1-9, wherein the at least oneserver computing device stores data that represents an associationbetween a user identifier of the user and the remittance; wherein the atleast one server computing device, in response to performance of the atleast one operation that provides the remittance to the user, storesdata that defines an association between a transaction identifier, anidentifier of user, and an amount of the remittance; and wherein, inresponse to the remittance being transferred to an account of the userand from an account controlled by an operator of a service provided bythe at least one server computing device, the at least one servercomputing device automatically destroys the data that defines theassociation between the transaction identifier, the identifier of user,and the amount of the remittance, such that the data that defines theassociation cannot be reconstructed.

Example 11: The system of any of Examples 1-10, wherein the at least oneserver computing device identifies, based at least in part onapplication of natural language processing to the descriptive data, anaccusation in a semantic meaning of the descriptive data; wherein the atleast one server computing device, in response to identification of theaccusation, identifies at least a portion of content in the descriptivedata that corresponds to the accusation; and wherein the at least oneserver computing device performs at least one operation to obfuscate atleast the portion of the content in the descriptive data.

Example 12: The system of any of Examples 1-11, wherein to perform theat least one operation, the at least one server computing device:generates data that associates a label with one or more of thedescriptive data or at least a portion of content in the descriptivedata; or modifies at least the portion of the content in the descriptivedata to change at least one of a character, pixel value, or sound of thedescriptive data.

Example 13: The system of any of Examples 1-12, wherein the at least oneserver computing device receives a crime profile comprising data thatcharacterizes the crime; wherein the at least one server computingdevice applies the data of the crime profile that characterizes thecrime to a bounty model that predicts a likelihood that a remittanceamount will produce information about the crime from one or more users;and wherein the at least one server computing device performs at leastone operation based at least in part on the likelihood that theremittance amount will produce information about the crime from one ormore users.

Example 14: The system of any of Examples 1-13, wherein the at least oneserver computing device selects a set of training instances, eachtraining instance comprising an association between a remittance amountand data that characterizes a crime; and wherein for each respectivetraining instance, the at least one server computing device, based on arespective remittance amount and respective data that characterizes acrime for the training instance, modifies the bounty model to change alikelihood predicted by the bounty model for a remittance amount inresponse to a subsequent crime profile applied to the bounty model.

Example 15: A method comprising: receiving, using an anonymizationnetwork and from a respective mobile computing device of a plurality ofmobile computing devices, a respective set of locations of therespective mobile computing device, such that the respective mobilecomputing device is anonymous to the at least one server computingdevice; generating, by a computing device and based at least in part ona determination that a location from the respective set of locations ofthe respective mobile computing device is within a threshold distance ofa location of a crime, a proximity indication that a user associatedwith the respective mobile computing device is proximate to the crime;in response to receiving an indication of a remittance for the crimefrom at least one other user, generating an association between theremittance and the crime; in response to receiving, using theanonymization network, descriptive data generated by the user that isdescriptive of the crime, sending the descriptive data to at least oneother mobile computing device of the plurality of mobile computingdevices that is associated with the at least one other user; andperforming at least one operation that provides the remittance to theuser in response to receiving, from the at least one other mobilecomputing device that outputs a user interface in which the descriptivedata is associated with the proximity indication, an indication torelease the remittance provided by the at least one other user.

Example 16: The method of Example 16, further comprising performing anyof the operations of any of the at least one server computing device inExamples 1-14.

Example 17: A computing device comprising one or more computerprocessors; and a memory comprising instructions that when executed bythe one or more computer processors cause the one or more computerprocessors to perform any of the method of Examples 15-16.

Example 18: A computer-readable storage medium encoded with instructionsthat, when executed, cause at least one processor to perform any of themethod of Examples 15-16.

Example 19: An apparatus comprising means for performing any of themethod of Examples 15-16.

Example 20: A method comprising: sending, using an anonymization networkand to a server computing device, a respective set of locations of amobile computing device, such that the mobile computing device isanonymous to the server computing device, and wherein the respective setof locations are usable by the server computing device to generate,based at least in part on a location from a set of locations beingwithin a threshold distance of a location of a crime, a proximityindication that a user associated with the mobile computing devices isproximate to the crime; in response to receiving an indication of aremittance for the crime from the server computing device,contemporaneously outputting for display an indication of the remittancein association with an indication of the crime; in response to receivingdescriptive data generated by the user that is descriptive of the crime,sending, using the anonymization network, the descriptive data to theserver computing device, and output a user interface in which thedescriptive data is associated with the proximity indication; and inresponse to receiving, from the server computing device, a message thatthe remittance is provided to the user, outputting for display anindication that the remittance is provided to the user.

Example 21: The method of Example 20, further comprising performing anyof the operations of any of the mobile computing devices in Examples1-14.

Example 22: A computing device comprising one or more computerprocessors; and a memory comprising instructions that when executed bythe one or more computer processors cause the one or more computerprocessors to perform any of the method of Examples 20-21.

Example 23: A computer-readable storage medium encoded with instructionsthat, when executed, cause at least one processor to perform any of themethod of Examples 20-12.

Example 24: An apparatus comprising means for performing any of themethod of Examples 20-21.

In one or more examples, the functions described above may beimplemented in hardware, software, firmware, or any combination thereof.If implemented in software, the functions may be stored on ortransmitted over, as one or more instructions or code, acomputer-readable medium and executed by a hardware-based processingunit. Computer-readable media may include computer-readable storagemedia, which corresponds to a tangible medium such as data storagemedia, or communication media including any medium that facilitatestransfer of a computer program from one place to another, e.g.,according to a communication protocol. In this manner, computer-readablemedia generally may correspond to (1) tangible computer-readable storagemedia, which is non-transitory or (2) a communication medium such as asignal or carrier wave. Data storage media may be any available mediathat can be accessed by one or more computers or one or more processorsto retrieve instructions, code and/or data structures for implementationof the techniques described in this disclosure. A computer programproduct may include a computer-readable medium.

By way of example, and not limitation, such computer-readable storagemedia can comprise RAM, ROM, EEPROM, compact disc read-only memory(CD-ROM) or other optical disk storage, magnetic disk storage, or othermagnetic storage components, flash memory, or any other medium that canbe used to store desired program code in the form of instructions ordata structures and that can be accessed by a computer. Also, anyconnection is properly termed a computer-readable medium. For example,if instructions are transmitted from a website, server, or other remotesource using a coaxial cable, fiber optic cable, twisted pair, digitalsubscriber line (DSL), or wireless technologies such as infrared, radio,and microwave, then the coaxial cable, fiber optic cable, twisted pair,DSL, or wireless technologies such as infrared, radio, and microwave areincluded in the definition of medium. It should be understood, however,that computer-readable storage media and data storage media do notinclude connections, carrier waves, signals, or other transient media,but are instead directed to non-transient, tangible storage medias. Diskand disc, as used, includes compact disc (CD), laser disc, optical disc,digital versatile disc (DVD), floppy disk and Blu-ray disc, where disksusually reproduce data magnetically, while discs reproduce dataoptically with lasers. Combinations of the above should also be includedwithin the scope of computer-readable media.

Instructions may be executed by one or more processors, such as one ormore digital signal processors (DSPs), general purpose microprocessors,application specific integrated circuits (ASICs), field programmablelogic arrays (FPGAs), or other equivalent integrated or discrete logiccircuitry. Accordingly, the term “processor,” as used may refer to anyof the foregoing structure or any other structure suitable forimplementation of the techniques described. In addition, in someaspects, the functionality described may be provided within dedicatedhardware and/or software modules. Also, the techniques could be fullyimplemented in one or more circuits or logic elements.

The techniques of this disclosure may be implemented in a wide varietyof devices or apparatuses, including a wireless handset, an integratedcircuit (IC) or a set of ICs (e.g., a chip set). Various components,modules, or units are described in this disclosure to emphasizefunctional aspects of devices configured to perform the disclosedtechniques, but do not necessarily require realization by differenthardware units. Rather, as described above, various units may becombined in a hardware unit or provided by a collection ofinteroperative hardware units, including one or more processors asdescribed above, in conjunction with suitable software and/or firmware.Various components, modules, or units are described in this disclosureas implemented within certain devices for examples purposes; however,such components, modules, or units may be implemented or distributed atone or more other devices to perform the functionality and/or producethe result of the components, modules, or units.

It is to be recognized that depending on the embodiment, certain acts orevents of any of the methods described herein can be performed in adifferent sequence, may be added, merged, or left out altogether (e.g.,not all described acts or events are necessary for the practice of themethod). Moreover, in certain embodiments, acts or events may beperformed concurrently, e.g., through multi-threaded processing,interrupt processing, or multiple processors, rather than sequentially.

In some examples, a computer-readable storage medium includes anon-transitory medium. In some examples, the term “non-transitory”indicates that the storage medium is not embodied in a carrier wave or apropagated signal. In certain examples, a non-transitory storage mediummay store data that can, over time, change (e.g., in RAM or cache).Although certain examples are described as outputting variousinformation for display, techniques of the disclosure may output suchinformation in other forms, such as audio, holographical, or hapticforms, to name only a few examples, in accordance with techniques of thedisclosure.

Various examples have been described. These and other examples arewithin the scope of the following claims.

What is claimed is:
 1. A system comprising: a first mobile computingdevice associated with a first user; a second computing device; at leastone server computing device communicatively coupled to the first mobilecomputing device, the at least one server configured to: interoperatewith the first mobile computing device on a network collectivelyadhering to a protocol, the at least one server configured to provide tothe first mobile computing device a first indication of a remittance fora particular event, wherein descriptive data from the first user that isdescriptive of the particular event is associated with the particularevent at the at least one server computing device; and after receiving asecond indication from the second computing device to configure theremittance with the particular event, send, to the first mobilecomputing device, information descriptive of the particular event forcontemporaneous display at the first mobile computing device with theremittance, wherein the descriptive data from the first user that isdescriptive of the particular event comprises information usable tosolve the at least one the of crime or suspected crime.
 2. The system ofclaim 1, wherein the first mobile computing device is configured toanonymously send the descriptive data to the at least one servercomputing device using an anonymization network; wherein theanonymization network comprises a plurality of relay network devices,wherein the plurality of relay network devices includes an ingress relaynetwork device communicatively coupled to the first mobile computingdevice, and the plurality of relay network devices comprises an egressrelay network device communicatively coupled to the at least one servercomputing device, and wherein a set of intermediate relay networkdevices in a communication route between the ingress and egress relaynetwork devices are configured to provide the communication routebetween the first mobile computing device and the at least one servercomputing device; wherein the descriptive data is received by theingress relay network device from the first mobile computing device, andwherein each relay network device in the set of relay network devices isconfigured to encrypt the descriptive data before the descriptive datais forwarded to another relay network device in the communication route;and wherein the egress relay network device is configured to decrypt thedescriptive data and forward the descriptive data to the at least oneserver computing device, such that the first mobile computing device isanonymous to the at least one server computing device.
 3. The system ofclaim 1, wherein the at least one server computing device is configuredto initiate a transaction that transfers at least a portion of an amountof electronic funds as the remittance to an account associated with thefirst user and from an account controlled by at least one of a seconduser or an operator of a service provided by the at least one servercomputing device.
 4. The system of claim 3, wherein the electronic fundscomprise cryptocurrency.
 5. The system of claim 1, whereincontemporaneous display at the first mobile computing device of theremittance with the information descriptive of the particular eventcomprises contemporaneous display of the remittance in association withlocation information of the particular event, wherein thecontemporaneous display of the remittance in association with locationinformation of the particular event is included in at least one of a mapgraphical user interface or a card graphical user interface element. 6.The system of claim 1, wherein contemporaneous display at the firstmobile computing device of the remittance with the informationdescriptive of the particular event comprises contemporaneous display ofthe remittance in association with information descriptive of one ormore visual characteristics of the particular event, wherein thecontemporaneous display of the remittance in association with theinformation descriptive of the one or more visual characteristics of theparticular event is included in at least one of a map graphical userinterface or a card graphical user interface element.
 7. The system ofclaim 1, wherein contemporaneous display at the first mobile computingdevice of the remittance with the information descriptive of theparticular event comprises contemporaneous display of the remittance inassociation with information descriptive of visual characteristics ofthe particular event, wherein the information descriptive of visualcharacteristics of the particular event describes one or more visualcharacteristics of a person with an allegation of committing an actassociated with the particular event.
 8. The system of claim 7, whereinthe at least one server computing device is configured to receive theinformation comprising the visual characteristics of the person with theallegation of committing the act associated with the particular eventfrom a third computing device configured to generate descriptive databased at least in part on textual input from a third user.
 9. The systemof claim 1, wherein the first mobile computing device is configured tooutput for display an indicator of the particular event on a map, theappearance of the indicator based at least in part on the remittance.10. The system of claim 1, wherein the first mobile computing device isconfigured to contemporaneously output for display, in a single userinterface, the remittance, a type of the particular event, locationinformation of the particular event, and the descriptive data from thefirst user that is descriptive of details of the particular event. 11.The system of claim 1: wherein the first mobile computing device isconfigured to receive, from the at least one server computing device,second descriptive data that is generated by at least one other user;and wherein the first mobile computing device is configured tocontemporaneously output for display the second descriptive data that isdescriptive of details of the particular event with the descriptive datafrom the first user that is descriptive of details of the particularevent.
 12. A non-transitory computer-readable storage medium comprisinginstructions that, when executed by one or more computer processors of aserver computing device, cause the one or more computer processors to:send to the first mobile computing device, via interoperation with thefirst mobile computing device on a network collectively adhering to aprotocol, a first indication of a remittance for a particular event,wherein descriptive data from the first user that is descriptive of theparticular event is associated with the particular event at the at leastone server computing device; and send to the first mobile computingdevice, after receiving a second indication from a second computingdevice to configure the remittance with the particular event,information descriptive of the particular event for contemporaneousdisplay at the first mobile computing device with the remittance,wherein the descriptive data from the first user that is descriptive ofthe particular event comprises information usable to solve the at leastone the of crime or suspected crime.
 13. The non-transitorycomputer-readable storage medium of claim 12, comprising instructionsthat, when executed by one or more computer processors of the servercomputing device, cause the one or more computer processors to initiatea transaction that transfers at least a portion of an amount ofelectronic funds as the remittance to an account associated with thefirst user and from an account controlled by at least one of a seconduser or an operator of a service provided by the at least one servercomputing device.
 14. A non-transitory computer-readable storage mediumcomprising instructions that, when executed by one or more computerprocessors of a mobile computing device, cause the one or more computerprocessors to: receive from the at least one server computing device,via interoperation with the at least one server computing device on anetwork collectively adhering to a protocol, a first indication of aremittance for a particular event, wherein descriptive data from thefirst user that is descriptive of the particular event is associatedwith the particular event at the at least one server computing device;and receive, after the at least one server computing device has receiveda second indication from a second computing device to configure theremittance with the particular event, information descriptive of theparticular event for contemporaneous display at the mobile computingdevice with the remittance, wherein the descriptive data from the firstuser that is descriptive of the particular event comprises informationusable to solve the at least one the of crime or suspected crime. 15.The non-transitory computer-readable storage medium of claim 14,comprising instructions that, when executed by the one or more computerprocessors of the mobile computing device, cause the one or morecomputer processors to contemporaneously display the remittance inassociation with location information of the particular event, whereinthe contemporaneous display of the remittance in association withlocation information of the particular event is included in at least oneof a map graphical user interface or a card graphical user interfaceelement.
 16. The non-transitory computer-readable storage medium ofclaim 14, comprising instructions that, when executed by the one or morecomputer processors of the mobile computing device, cause the one ormore computer processors to contemporaneously display the remittance inassociation with information descriptive of one or more visualcharacteristics of the particular event, wherein the contemporaneousdisplay of the remittance in association with the informationdescriptive of the one or more visual characteristics of the particularevent is included in at least one of a map graphical user interface or acard graphical user interface element.
 17. The non-transitorycomputer-readable storage medium of claim 14, comprising instructionsthat, when executed by the one or more computer processors of the mobilecomputing device, cause the one or more computer processors tocontemporaneously display the remittance in association with informationdescriptive of visual characteristics of the particular event, whereinthe information descriptive of visual characteristics of the particularevent describes one or more visual characteristics of a person with anallegation of committing an act associated with the particular event.18. The non-transitory computer-readable storage medium of claim 14,comprising instructions that, when executed by the one or more computerprocessors of the mobile computing device, cause the one or morecomputer processors to output for display an indicator of the particularevent on a map, the appearance of the indicator based at least in parton the remittance.
 19. The non-transitory computer-readable storagemedium of claim 14, comprising instructions that, when executed by theone or more computer processors of the mobile computing device, causethe one or more computer processors to output for display, in a singleuser interface, the remittance, a type of the particular event, locationinformation of the particular event, and the descriptive data from thefirst user that is descriptive of details of the particular event. 20.The non-transitory computer-readable storage medium of claim 14,comprising instructions that, when executed by the one or more computerprocessors of the mobile computing device, cause the one or morecomputer processors to: receive, from the at least one server computingdevice, second descriptive data that is generated by at least one otheruser; and contemporaneously output for display the second descriptivedata that is descriptive of details of the particular event with thedescriptive data from the first user that is descriptive of details ofthe particular event.